Bus Tour 2026 - Articles of Interest by TOP Venture

Articles of Interest Silicon Valley Bus Tour 2026 Background reading on the entrepreneurs, executives, and investors we will meet along the way.

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Disclaimer IMPORTANT

The content of this section has been issued for information purposes only. The information and opinions contained in this document are for background information and discussion purposes only and do not purport to be full or complete. No information in this document should be construed as providing financial, investment or other professional advice. This information contained herein is for the sole use of its intended recipient and may not be copied or otherwise distributed or published without the Fund’s express consent. No reliance may be placed for any purpose on the information contained in this document or their accuracy or completeness. Information included in this document is intended for those investors who meet the Qualified Investors definition of the Collective Investment Schemes Act of 23 June 2006 and its ordinance and the Financial Conduct Authority definition of Professional Client or Eligible Counterparty.

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Reading List Grouped by company, in alphabetical order.

COMPANY

MEETING WITH

ARTICLE

PAGE

Arena

Suchit Dash

In The Arena

Anu Hariharan

Inside the Secret School for the World’s Best Founders

Alex Bouaziz, CEO of Deel, on Deel’s bundleunbundle strategy

Sneha Revanur ’26, founder of Encode Justice, advocates for youth voice in AI regulation

Sneha Revanur on how a small team of activists helped pass America’s landmark AI safety laws

There is exactly one way that SaaS can be saved

The age of vertical models is here

Unlocking Customer Lifetime Value and Embracing AI with Google’s Neil Hoyne

Communities, companies, and consumers: How AI can do good

Avra

Felicis · 4 March 2026

The Generalist · 3 October 2024

Deel

Joe Kauffman

Sacra · 5 November 2025

Encode AI

Sneha Revanur

The Williams Record · 10 May 2023

80,000 Hours Podcast · 8 July 2026

Fin

Dan Griggs

Fin Ideas · 2 March 2026

Fin Ideas · 26 March 2026

Google

Neil Hoyne

Sidecar Sync Podcast · 19 April 2024

Google

Gopi Kallayil

I by IMD · 7 April 2025

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COMPANY

MEETING WITH

ARTICLE

PAGE

Netflix

Kate Norton

Freedom, Fear, and Feedback: Should Other Companies Follow Netflix’s Lead?

How Netflix is using AI to personalize streaming

How I learned to stop worrying and love AI

Notion’s Ivan Zhao: The Refounder

Coming to America

New CFO signals disciplined ambition for Nubank’s next phase of growth

Justin Ferrell is the essential voice for designthinking in organizations

Stanford merges AI and data science efforts under single institute

Pulling back the curtain on the magic of Y Combinator

20 years & 125 million subscribers later…

From the CEO: What’s coming to YouTube in 2026

YouTube Is Battling Netflix Over Top Talent

HBS Working Knowledge · 6 August 2025 Fortune · 29 September 2026

Notion

Elias Rimer

Notion Blog · 30 September 2024

Sequoia Capital · Long Strange Trip podcast

Nubank

Rob Livingston

Colossus · October 2026

Nu Newsroom · 6 August 2026

Stanford

Justin Ferrell

Dialogue Review · 16 October 2019

Stanford

James Landay

Stanford Report · 4 May 2026

Y Combinator

Grey Baker

Lenny’s Newsletter · 11 February 2025

YouTube

Will Aldrich

YouTube Official Blog · 5 March 2025

YouTube Official Blog · 21 January 2026

The Wall Street Journal · 23 September 2026

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AREA

Tue 13 Oct

San Francisco

Suchit Dash Chief Product Officer, Arena

ARTICLE 1

FELICIS · 4 MAR 2026 · MATT QUINN

In The Arena How Anastasios Angelopoulos and Wei-Lin Chiang Built AI’s Most Trusted AI Evaluation Platform

Anastasios Angelopoulos and Wei-Lin Chiang

It was around spring 2024 when friends noticed that PhD student Wei-Lin Chiang had begun carrying his laptop everywhere. Suddenly, it was his constant companion at every meal, gathering, and errand. “He wanted to make sure that if something broke, he could get it back online,” says his research partner, Anastasios Angelopoulos. “Growing the platform was really a labor of love for him.” While PhD students at the University of California, Berkeley, the pair had created Arena (then known as “Chatbot Arena”) as part of a research project to rank chatbots based on S T R I C T LY C O N F I D E N T I A L

human preference. On the site, a user would enter a prompt, receive responses from two anonymous models, pick which response they liked better, and then the bots’ identities were revealed. That raw, crowdsourced data then fed into a leaderboard that ranked publicly available models. The project’s timing was auspicious. After years of development in academic and frontier labs, large language models were delivering on AI’s hype. Prompts and queries produced human-like output and bots could (mostly) follow along in conversations. Competition to claim the “best” or “SOTA” model was heating up among frontier labs, giving

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Chatbot Arena users no shortage of models to test and vote on. The research portion of the project had ended, but the site had taken on a life of its own. The users kept coming back. Tens of thousands of people a month from around the world used it to try out different models. Frontier labs had taken notice and begun to test models on the site before their public release. Site traffic kept growing. Wei-Lin and Anastasios found their lives suddenly changing to accommodate the project’s needs. They worked such long hours that they moved in together. Vacations were out of the question. It became clear they had a decision to make. “I pivoted entirely from my previous research to just doing this Arena project,” says Wei-Lin. “We were at a very critical moment. We had to decide, is this just a research project we wind down? Or is this something more?” An academic pursuit becomes a market

Wei-Lin had never intended to build AI products, let alone evaluate the underlying technology. Under Ion Stoica, his advisor and the director of UC Berkeley’s Sky Computing Lab, his previous work at Berkeley had centered on systems, including a project called SkyPilot and another around reinforcement learning for optimizing database systems. But when OpenAI released its public preview of ChatGPT in late 2022, the floodgates opened. New models, breakthroughs, and, most importantly, opportunity emerged. “It completely changed how I think about the future and how AI could impact the real world,” says Wei-Lin, who was in the third year of his PhD work when ChatGPT made its debut. “The question for me became, ‘How can I do research that’s relevant to this?’” To figure that out, Wei-Lin first needed to understand the technology’s capabilities and limitations. Over the course of about four months, Wei-Lin and a group of fellow students created Vicuna, an open source chatbot built by training Meta AI’s LLaMA on conversations that users had with ChatGPT and then shared on a public forum. “We were just a bunch of PhD students working together as a weekend project, building a prototype,” Wei-Lin says. But Wei-Lin and his fellow students weren’t the only ones building their own models. They wanted a way to prove that the model they’d built performed better than others, especially one in particular.

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“Stanford actually had their own version of this open source chatbot, and we wanted to prove that ours is better – basically that Berkeley is better than Stanford,” says WeiLin, laughing. For the initial work, the team fed queries and responses from the chatbots they were assessing into ChatGPT and let it decide which was best. They hoped to leverage the advancements in OpenAI’s model to automate the evaluation process. The method demonstrated some potential, but it lacked sufficient rigor. As the team wrote in a blog at the time, “Building an evaluation system for chatbots remains an open question requiring further research.” As AI technology has advanced, the demand for reliable evaluation and benchmarking tools has skyrocketed. Many benchmarks are static: multiple-choice questions or tasks with predefined answers. These tools are invaluable to the researchers building AI systems, and benchmarking scores unquestionably offer an important signal to users. But they’re also easy to game, incentivizing teams to build for benchmark scores that demonstrate a model’s mastery of certain subjects and abilities, while ignoring real-world applications. It’s the AI version of teaching to test. As increasingly capable chatbots flooded the market, Wei-Lin was struck by the shortcomings of existing evaluation methods. With Ion advising him, Wei-Lin enlisted his fellow students to compare how an LLM’s evaluation choices stacked up against human preferences. This became the first version of Chatbot Arena. The project took off: in just one month, Chatbot Arena logged 30,000 votes, well beyond the group’s expectations. The research produced a paper, but more importantly, a spark. Wei-Lin wanted to keep going. A shared fixation on seeking truth

The problem of how to measure the real-world performance of AI was also on Anastasios’s mind after ChatGPT debuted. At the time, his PhD research focused on how to use statistical and mathematical methods to make machine learning models more reliable. Anastasios knew AI would change the world, and he wanted to help make it more reliable. “That's why evaluation was a good fit for me. Evaluation is all about, how do you measure things properly, and how do you make statistically valid claims about model performance that are really supported by evidence?” he says. His advisor, UC Berkeley statistical machine learning

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luminary Michael I. Jordan, connected him with Wei-Lin and Ion as they plotted next steps for Chatbot Arena. Foundations for the research were in place when Anastasios joined with relatively modest expectations.

data through Arena than any other benchmark in the world. So when people ask about the leaderboard and provide feedback, we're always open to it, and we hope to earn trust with the community through that transparency.”

“Wei-Lin and the rest of the team working on the project were all super smart, but the platform was not close to what it is now, in any sense,” he recalls. “It was like an early-stage research project. At the end of the day, we thought it was going to be a paper, not a company.”

Ion, with deep founder experience from Databricks and Anyscale, also felt the shift that came with the attention from the labs and influential tech figures like Andrej Karpathy, Jeff Dean, Elon Musk, and Sundar Pichai. He continued to work closely with Wei-Lin and Anastasios, noting their “conviction, drive, and a great balance between technical depth and ability to inspire and lead the community.”

After the Chatbot Arena paper was published in March 2024, many of the students involved moved on and returned to their own research. But the work had become something more to Wei-Lin and Anastasios. They didn’t feel done with the project; on the contrary, it was taking up more and more of their lives. Their partnership had deepened, too: they realized they shared a fixation on seeking truth. And traffic to the site just kept growing. They knew they had a decision to make. Measuring and advancing the AI frontier

Around the time that Wei-Lin began bringing his laptop everywhere, OpenAI researchers brought them a mystery model to test on the site. Later, it was revealed as a prerelease of ChatGPT 4. The impact was instant. “GPT 4 released and our traffic basically went 10X,” says Anastasios. “And then a lot of those users stayed.” OpenAI debuting a new model on Chatbot Arena sent a clear message to the team: the leaderboard had found a place in the burgeoning AI ecosystem. Something had fundamentally changed. The scope of the project had expanded, and so had their ambitions. “That was a huge deal to us. It wasn’t just a research project anymore,” says Wei-Lin. “They actually cared about us. They cared about the leaderboard.” Beyond the interest from frontier labs, Wei-Lin and Anastasios believed that, as academics, they could build something that users could trust, even as their platform faced scrutiny that intensified along with its popularity. “I believed there was something unique we could do at the lab,” Wei-Lin says. “We were in a very different position than the frontier labs. We could be an academic voice for measuring models for the community. That sounded durable to me.” “The fact that our leaderboard is an open source methodology means that anybody on the internet can go look and see how the leaderboard is calculated,” says Anastasios. “We have probably open-sourced more organic conversation S T R I C T LY C O N F I D E N T I A L

In September 2024, Anastasios and Wei-Lin migrated Chatbot Arena away from the Berkeley-backed site it had been on to its own home, lmarena.ai, and changed its name to “LMArena.” The move gave them increased independence and set the stage to expand leaderboard rankings beyond chatbots. Image Arena, Search Arena, Video Arena, WebDev Arena, and others were soon added. As Anastasios, Wei-Lin, and Ion debated what came next for LMArena, maintaining neutrality and scientific integrity were non-negotiable. But ultimately, they wanted to create something that could provide real value by evaluating the reliability of any AI model. “We felt that if we didn't start a company, we would be resource-starved,” says Anastasios. “We would not be able to recruit the best people and gather the financial resources needed in order to support a platform that really did the best evaluations at that scale without starting a company. And so it became existential. We either do this or the forum likely won't survive.” So in April 2025, they incorporated LMArena. Side by Side Mode

Under LMArena’s new structure, Anastasios was named CEO, Wei-Lin became CTO, and Ion assumed the role of chairman. LMArena continued to move as fast as the technology they’re measuring. They’ve already been through a corporate name change (now rebranded “Arena”) and two fundraising rounds (Felicis participated in their Seed Round and led their Series A). Last fall, Arena launched its first commercial product, AI Evaluations, a service for enterprises, model labs, and developers to understand how their products perform in the real world. Moving from the lab to revenue so quickly is a reflection of the position Arena has already cemented in the AI value

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chain. As Felicis General Partner and Arena board observer Peter Deng points out, consumers use Arena because it gives them free access to the newest and most powerful models, often before broad release, and the ability to evaluate frontier AI directly. The model labs gain high-quality, realworld evaluation data. “As a result, Arena has become the backbone of how the world understands and advances AI,” says Deng. Ion has been instrumental in helping the two founders find their footing, even serving as Arena’s interim head of machine learning. “Ion treats us as equals,” says Anastasios. “He treats us like our opinions really matter, he listens very carefully, and he will contribute his thoughts and we'll have debates and discussions and arguments—in a good way.” And while Anastasios and Wei-Lin are no longer roommates, their friendship has only strengthened. They love sharing dinner together, along with their partners, especially over Wei-Lin’s “world famous” hot-pot. The most important part of their relationship is the trust they’ve formed. “We spend every day talking to each other about some of the most important career decisions and financial decisions of our lives, so we’d better trust one another,” says Anastasios. “Part of that is having no ego. We basically have to never put ourselves before the company.”

“

The founders find themselves in a slightly surreal position. Anastasios had imagined he would strike out on his own one day, but that wasn’t the plan when he joined Wei-Lin’s project just a couple of years ago. “If not for this, I would have been a professor right now,” he says. “I still hope to keep my academic roots, but right now I’m just on an unexpected and happy path.” That path was made possible by the overabundance of AI models that continue to emerge. As AI gets more powerful and spreads into more facets of life and the economy, ensuring its reliability will only become more critical. With that in mind, Anastasios, Wei-Lin, and Ion will grow and shape Arena with the aim of making it into the world's evaluation infrastructure. “AI is the most important technology of our lifetimes, and potentially one of the most important technologies ever, in the same category as agriculture and electricity and the internet,” says Anastasios. “We really have a responsibility to make sure AI develops in a reliable way that's aligned with human values. And you can't understand or improve what you can't measure. That’s where Arena sits.”

We really have a responsibility to make sure AI develops in a reliable way that’s aligned with human values. And you can’t understand or improve what you can’t measure. Anastasios Angelopoulos, Arena Co-Founder and CEO

SOURCE

Read the Original felicis.com/blog/founder-profile-arenas-anastasios-angelopoulos-and-wei-lin-chian g Felicis, 4 March 2026. Reproduced in TOP Venture format for LP reference.

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AREA

Thu 15 Oct

San Francisco

Anu Hariharan Founder & Managing Partner, Avra

ARTICLE 2

THE GENERALIST · 3 OCT 2024 · MARIO GABRIELE

Inside the Secret School for the World’s Best Founders Avra, run by former Y Combinator investors, keeps a low profile. It’s quickly becoming a critical partner for elite entrepreneurs.

Illustration: Ibrahim Rayintakath

If you only have a few minutes to spare, here’s what investors, operators, and founders should know about Avra. 1 The school for scale. Founded in 2023, Avra runs a

selective program for the world’s best growth-stage entrepreneurs. It helps the leaders of breakout businesses learn how to build an executive team, maintain shipping speed, and plan for the future. It’s a kind of doctoral program for startup CEOs, albeit one with a well-guarded curriculum and a venture fund on the back end.

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2 Learning from Y Combinator. Avra’s team previously

worked together at YC Continuity, the growth practice of the famed accelerator. When YC suddenly shuttered that division in March 2023, Avra founder Anu Hariharan put her plans for a new growth program into high gear, bringing colleagues with her.

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3 A missing piece. Though YC is still recognized as the

best launchpad for early-stage startups, it has competition from dozens of other incubators and accelerators. Avra is the first of its kind: a high-quality standalone program for post-Series A companies. As a result, the fund has the opportunity to establish itself as a standard bearer for later stage startups.

4 Tactical masterclasses. Avra’s program is taught by

some of the startup ecosystem’s most impressive and successful founders. Sessions cover choosing the right metrics, hiring executives, scaling engineering, leveling up financial planning, and preparing for future fundraises. Each one is a tactical masterclass full of detail.

5 Reordering VC. Though Avra’s principal mission is to

assist founders through targeted education, it monetizes as a venture firm. It is raising a reported $350 million to invest in a small fraction of the startups that pass through its program. It’s a clever strategy that reorders the traditional sequence venture capital follows. Rather than winning a deal and then adding value, Avra does the work upfront, proving its impact and building rapport ahead of a future round.

Benedict Evans, analyst and erstwhile investor, once referred to Andreessen Horowitz as “a media company that monetizes through VC.” It was a pithy description of his former employer that got to the heart of the firm’s forceful brand building strategy. Avra Capital is a trade school that monetizes through VC. In almost all of its core functionality, Avra appears to be a small-batch institution of higher learning. It runs bi-annual cohorts, holds classes, doles out required reading, and assigns homework. What distinguishes Avra from other vocational programs is the trade that it teaches, and the student body it admits. Avra is not focused on nursing, HVAC repair, or aeronautics but on the craft of company building. Its student body is made up of many of this generation’s most promising founders—the people behind some of the world’s hottest startups, vying to become tech’s next big winner. All matriculate to learn directly from founders who have overcome the obstacles they currently face. Walk the imagined hallways of Avra Academy, and you’ll pass the bronze nameplates of its luminary educators: Professor S T R I C T LY C O N F I D E N T I A L

Parker Conrad of Compound Software, Visiting Scholar Greg Schott of Enterprise Sales, and Dean Tony Xu, Head of Urban Scanning. Avra’s top-tier instructors and effective playbook owe a great deal to the experience of its founder, Anu Hariharan. Starting in 2016, Hariharan ran Y Combinator’s Growth team, backing companies like Brex, Monzo, Gusto, Zepto, Groww, Rappi and Faire. As part of that role, she and co-head Ali Rowghani managed the accelerator’s post-Series A program, designed to help breakout companies manage the next phase of their growth. When YC President Garry Tan abruptly shut down the division in March 2023, Hariharan and several colleagues used seven years of lessons to found Avra. Given Hariharan’s bonafides and the quality of Avra’s instruction, it’s little wonder that attaining entrance to the fund’s program has grown increasingly competitive in just its first year of operation. The chance to attend small, tactical sessions with legendary entrepreneurs is attractive to many – not least when delivered in the vulnerable, off-the-record style that Avra encourages. It wants its students not simply to understand how DoorDash’s CEO recruits his C-Suite, for example, but to hear the mistakes and lessons learned along the way. That frankness is why Avra guards the content of its curriculum so closely. It is one thing to ask a founder to regale an audience of junior peers with a parade of mistakes, quite another to make those battle scars visible to the public. Perhaps because of its combination of secrecy and cache, Avra (and YC Growth before it) represents a tantalizing prospect for outsiders. Visit its site, and you’ll find glowing testimonials from alumni but little in the way of tangible detail. How do great CEOs scale their engineering teams? What quirks enable tech companies to maintain a rapid shipping speed? In short, what does a school for superscalers actually look like from the inside? What do exceptional founders know that the rest of us don’t? Over the past nine months, The Generalist has been given unprecedented access to Avra’s program, experiencing it as a student might. That includes accessing its classes, program material, and alumni resources. It proved an illuminating process, giving me insight into Avra’s unusual advantages in the venture landscape and a fiercer appreciation for the grit, guile, intensity, and consistency it takes to build a generational business.

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The making of a VC

Anu Hariharan made her decision. After much deliberation and research, she’d elected to choose three promising growth-stage companies: online grocery delivery provider Instacart, travel marketplace GetYourGuide, and on-demand storage player MakeSpace. It represented an unusual sort of investment decision—freighted by high stakes but with no money on the line. It was part of the interview process with a New York City hedge fund interested in venture investing —“you can probably easily guess who,” she says— and Hariharan had been tasked with pitching a trio of compelling Series B startups. It was a tricky task for a former Qualcomm engineer and Boston Consulting Group principal with no venture capital experience and little familiarity with the tech landscape. “I didn’t even know what Series B was,” Hariharan recalled. “I didn’t know anything about startups. I didn’t even read TechCrunch.” Eleven years later, we know that Hariharan picked well. Instacart was valued at $25.4 million in its 2013 Series A; today, it trades at $9.5 billion. The Berlin-based GetYourGuide raised $194 million in debt and equity in 2023 at a $2 billion valuation; it had raised approximately $20 million at the time Hariharan assessed it. Only MakeSpace can be considered a miss, merging with rival firm Clutter, which subsequently sold at a steep discount last year. Unsure of her selections and eager for a more experienced opinion, Hariharan reached out to seasoned investors, asking for their advice. That act summarized Hariharan’s direct, unmappable approach to problem solving, and changed the course of her career. “I sent cold emails to four VCs saying, “I’m interviewing at this fund, and I would love any feedback on the three companies I’ve picked to pitch,’” Hariharan recalled. “One of the people I emailed happened to be Jeff Jordan.” As it turned out, Jordan was the perfect recipient for Hariharan’s message. Not only had he spent time at BCG before rising through the ranks at Disney, stepping in as President of PayPal, co-founding OpenTable and Wealthfront, and arriving at Andreessen Horowitz (a16z), but he was also actively researching Instacart. “I didn’t realize that he was diligencing them for the Series B,” Hariharan said. “He thought my diligence was pretty good and pretty interesting, so we started going back and forth on emails. And then he said, “Whenever you’re in San Francisco next, I’d love to meet you.” S T R I C T LY C O N F I D E N T I A L

Rather than leave the encounter to fate, Hariharan said she’d be in town the next week and booked a ticket. When she arrived at a16z’s office, Jordan surprised her with a few additions to her agenda. “I thought I was meeting just him, but he’d arranged eight meetings for me with everyone else at the firm,” Hariharan said. Shortly after, Hariharan was offered a job on a16z’s investment team. It marked the beginning of her venture career and the start of a breakneck education in a new kind of investing. Though Hariharan had spent much of her time at BCG in the firm’s private equity practice, conducting detailed due diligence on potential investments, VC required her to adjust her perspective. “I had to recalibrate my thought process from PE to VC. After every pitch meeting, Jeff would ask me to articulate my point of view within five minutes. He also helped me focus on how to identify founders because so much of venture is about picking the right person.” In addition to paying closer attention to entrepreneurs, Hariharan had to learn to let go of some of the conservatism her private equity experience had inculcated in her. A lunch meeting with firm co-founder Marc Andreessen encouraged her to focus more on a company’s potential than its risks. “It was sometime around my nine-month mark at a16z,” Hariharan recalled. “He told me that usually, when he onboards someone, he has to teach them not to say yes to too many investments. But for me, he was going to have to teach me to say yes to one of them.” Andreessen told her that a VC’s biggest mistakes were ones of omission – the great companies that you should have invested in but didn’t. He urged Hariharan to apply her analytical brain to investigating a startup’s upside, developing the conviction to take a swing. Hariharan cites Chris Dixon and Ben Horowitz as additional influences during this stage of her venture schooling. “Ben is exceptional at B2B SaaS – I learned a lot from how he dug into whether a sales team was working and the go-to-market metrics. Chris is just one of the most intelligent thesis-based investors I’ve ever seen.” Hariharan took lessons from both of them. Although Hariharan may have been a greenhorn when it came to the venture asset class, she entered the industry with technical expertise, strategic experience, and a natural

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nose for investing. She tells the story of her entry into venture capital with deep humility – casting herself as a learner, above all else – but Hariharan’s fast rise is a testament to her talents. Spend even a few minutes with her, and you cannot help but notice her striking but unmashy intellect, a direct, genial speaking style, and substance. Her long-time colleague Nic Dardenne summarized Hariharan’s gifts eloquently. “There are two things: one, she works insanely hard. She’s an incredibly successful person but is also the hardest-working person I know, both for the team and the founders she works with. Two, she does right by founders. She has this superpower of telling people what they need to hear, not what they want to hear, but doing so in a way that endears herself to them and makes them trust her even more.” Not long into her second year at a16z and another Silicon Valley institution had started noticing her talents. Sam Altman, then President of Y Combinator, had decided to launch a growth practice designed to double down on the accelerator’s best-performing businesses. He sought two general partners to run “YC Continuity,” with existing Managing Director Ali Rowghani—the former CFO and COO of Twitter—slated to step into one of those roles. Despite her relatively short tenure in venture, Hariharan had already made an impact on the YC community, developing a relationship with several of the ecosystem’s startups. “We worked with a lot of YC founders at Andreessen Horowitz,” she said. “One of YC’s partners pinged me and said they’d heard my name a lot and asked if I’d be open to having a conversation about the growth fund they were planning to launch.” She was. Though Hariharan enjoyed her time at a16z, there was no path to a partner at the time – significant for someone who had been on the partner track at BCG. After she completed a two-year stint, she planned to step into an operating role at one of the firm’s portfolio companies. “I was on the path to be the CFO of one of the startups we’d invested in,” Hariharan reflected. “I never felt like I needed to be an investor. My goal is always around learning and impact. I thought, ‘Maybe I can go to a portfolio company and do that for four or five years.’” Altman’s interest forced her to reconsider that plan. “YC is such an amazing place and a very differentiated platform,” Hariharan said. “I think it’s unlike any other VC. It’s not really

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a VC fund.” Over a few months, Hariharan got to know the team better, and by August 2016, she’d decided to join as YC Continuity’s second managing director. Continuity

Though Hariharan intended to stay four years at Y Combinator, she lasted seven. That duration is a consequence of the compelling power of YC’s platform, the value the Continuity practice created, and the abruptness with which it was shuttered. But we should not rush ahead. When Hariharan joined Ali Rowghani in 2016, the pair were tasked with building out a new practice under the auspices of Y Combinator. In addition to functioning as a growth-stage investor, Continuity was expected to build a curriculum and operate a program of its own. Much of that mission aligned with Y Combinator’s roots, of course. Ever since its founding in 2005, it had operated a defacto “founder school,” teaching unseasoned founders how to build startups. Its syllabus – devised by Paul Graham and honed by countless partners and practitioners – accelerated the trajectories of companies like Reddit, Airbnb, Stripe, and Flexport. Continuity would do the same, albeit for a different audience and with some critical tweaks. Rather than assisting scarcely-formed projects, it would work with established startups, rapidly scaling revenue and headcount. That contrasting focus necessitated changes to YC’s classic syllabus and the program's structure. Instead of serving 50, 100, or even 400 startups a batch, Continuity worked with 8-12. Rather than focusing on finding product-market fit, Hariharan and Rowghani counseled founders on scaling as CEOs, hiring executives, maintaining shipping speed, plowing through plateauing growth, and raising later-stage rounds. And because those topics require detailed tactical knowledge and emotional credibility, Continuity primarily relied on active founders – those still “in the arena” – to teach its courses. Plaid’s Zach Perret and Webflow’s Vlad Magalin both taught for Hariharan’s program. It is perhaps unsurprising that Continuity proved a hit, with founders across YC’s ecosystem jockeying for entrance. It didn’t hurt that the growth program stood alone in the competitive landscape. Although myriad accelerators like Techstars and 500 Startups had cropped up to vie for earlystage founders, no dominant program existed for scalers. “I 12

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don’t think anyone runs something similar,” Hariharan said. “Even now that I’m on the outside and have spent all this time learning about founder programs, I still haven’t found anyone who does it – at least not as well.” In part, that’s because of the network and wisdom Continuity was able to glean from its parent company. “I think we learned the art of doing it well because we got to see how well YC did it for the early stage,” Hariharan reasoned. “It’s not easy to do without that.” Though Continuity saw itself principally as an educator, it monetized like YC – via investments. Once again, it did so with a twist. While YC makes investment a requirement to participate – you cannot attend the program without accepting its “Standard Deal” – Continuity operated opportunistically, investing in a select number of companies only when the right moment arrived. Not only was this a logical reflection of later-stage funding rounds, but it also meant that companies that matriculated to Continuity did so with no strings attached. The vast majority of graduates never received capital from Hariharan and Rowghani; of the approximately 180 that went through the program, Continuity backed just a fraction of them. As she had at a16z, Hariharan continued to learn from those around her, not least future OpenAI’s supreme leader, Sam Altman. In particular, Altman exhorted Hariharan to test her conviction and size bets aggressively. “Sam had this characteristic of asking, ‘Are you betting the house?’” Hariharan recalled. “It was his way of understanding if you had high conviction on an investment. Either you have full conviction, or you don’t. If you’re on the fence, why are you doing this? And if you have full conviction, why aren’t you doing more? It’s a simplistic framework, but I appreciate how much clarity it brings to investment decisions. That’s the biggest thing I learned from Sam.” According to Hariharan, Altman’s heuristic made a noticeable difference on Continuity’s investing style over time. In its first fund, the growth team approached capital-intensive businesses cautiously, even if a large addressable market might have justified a bolder strategy. By its last fund, Continuity had learned to lean in. “We were a little gun shy when the risk was higher, but then by the third fund, we were more aggressive. When we saw Zepto, which is a 10-minute quick commerce player in India, we bet the house. It wasn’t clear it was going to be a breakout, but it is today.” Hariharan and Rowghani were not alone in making these investment decisions. Their growth practice grew to include Nic Dardenne, a former Morgan Stanley investment banker, S T R I C T LY C O N F I D E N T I A L

and Tiffany Kosolcharoen, who conducted market intelligence at Meta. Dardenne operated as a traditional growth investor, albeit one with a particular gift for grasping a company’s financials. A colleague likened his role to that of a “mini CFO” for some of the companies he works with, helping to retool their models from the ground up. Kosolcharoen served in a slightly different capacity. At Meta, she built out the market intelligence systems and conducted research for a portfolio of products. At YC Continuity, she was brought on as Head of Investment Research, tasked with monitoring the accelerator’s many companies and spotting candidates for additional capital. Through this process, Continuity quickly spotted the steep trajectory of startups like Deel and Zip before they raised Series A rounds. That allowed the Continuity team to build a relationship and lead later investments. Over Continuity’s seven-year run, it pulled together a promising portfolio, many of which have repaid its investment many times over. Hariharan and Rowghani’s prominent bets include Stripe, Coinbase, Faire, Monzo, Groww, Vanta, Segment, Rappi, Gusto, and Brex. Naturally, not all have been hits – in October 2023, trucking firm Convoy, a Continuity investment, shut down operations after consuming over $1 billion in capital. Nevertheless, on balance, Hariharan’s team seems to have done remarkably well. “My hope is that in time, we’ll show that we had one of the best growth track records during that period,” Tiffany Kosolcharoen said. Brex represented a particularly significant investment for Hariharan. Not only did she preempt a pricey Series B round for a company that had little revenue in 2018 – a decision that was spectacularly vindicated in the following years— but she also found a future colleague. Serving on Brex’s board introduced her to Lucas Fox, an early employee who would go on to manage its startup business unit. The pair became frequent collaborators, with Fox struck by the intensity with which Hariharan was willing to graft on behalf of the company. “She was almost like an exec at Brex. We worked really closely together – we’d go on three-to-fiveday work binges when we were trying to solve a problem together.” Sometimes, when Fox was tackling a particularly thorny issue, he’d stay at Hariharan’s family home for days at a time. That level of commitment, combined with the value of its 13

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programming, forged an unusually strong bond between Continuity’s principals and the startups it served. One founder who went through the course described it as “one of the most valuable things I’ve done as a CEO.” Overall, YC’s growth program earned an NPS of 70+ from founders, an illustration of the esteem in which it was held. All of which made its sudden demise even more startling. The last job

If there was one source of friction between Anu Hariharan and Y Combinator, one wasp at the picnic, this was it. The accelerator wanted Continuity to invest only in startups that had gone through its early-stage program. Its mission was to prepare YC alumni for the next phase of growth and build greater ownership in their businesses, not accelerate the best growth founders, no matter what their provenance. It marked a philosophical difference between Hariharan and her employer. Though she understood that accepting non-YC companies presented a challenge – risking upsetting legacy founders in favor of newcomers, she considered it a surmountable one. “I actually told YC that maybe the program should include companies from the outside. Just like when you look at universities, there are two main entry points: undergraduate and graduate,” said Hariharan. YC dabbled with the idea, allowing Continuity to back two external startups: British neobank Monzo and the ill-fated logistics company Convoy. Ultimately, though, it declined to continue the experiment, preferring to exclusively serve alumni. Long before Hariharan joined Continuity or even a16z, she’d known that, at some point, she wanted to build a business of her own. “I’ve always had the itch to be an entrepreneur. I didn’t know whether I would start a company or a fund, but I knew that my last job could never be part of any platform.” The limitations on Continuity’s operations, added to the fact that she’d stayed at YC much longer than she’d anticipated, caused Hariharan to consider building something of her own. By the end of 2022, she’d written a “strategy letter” outlining the fund she planned to start. It would be a firm influenced by the impact of YC Continuity but available to all founders. “I thought that what we built at YC was awesome, and I really wanted to continue that work,” Hariharan explained. “Barring a few, growth investing on the outside is done so poorly. It’s done lazily. Everyone thinks, “Oh, these companies have their Series A, that’s enough. They have $5S T R I C T LY C O N F I D E N T I A L

15 million in revenue; they don’t need support.’ That’s absolutely not true. I felt there was an opportunity to do this really well, inspired by all the YC principles I learned, but to do it differently.” There’s a long-standing joke in the Hariharan family: every financial recession comes for Anu. She graduated college in the wake of the dotcom crash, then received her MBA amidst the wreckage of the global financial crisis. But as America mirted with another downturn at the start of 2023 and Silicon Valley weathered a banking crisis, the Hariharans were uncommonly sanguine. “My family thought, ‘Oh, in 2023, Anu is safe; she has so many years of experience,’” Hariharan says with a chuckle. “And then, of everyone in the family, I was the only one without a job.” The defenestration of Hariharan, Rowghani, and the rest of the Continuity team was swift. On March 13, 2023, The Information reported that new YC president Garry Tan had decided to close the firm’s growth practice as part of a push to refocus the accelerator. “Late-stage investing turned out to be so different from early-stage investing that we found it to be a distraction from our core mission,” Tan told The Information at the time. It came as a jolt to Hariharan. Though she’d laid the groundwork for a new fund, she hadn’t expected to take the jump until 2024 at the earliest. Now, the transition had been thrust upon her. “It was hard, she said. “We had to take care of the whole team. It was a huge shock to them.” At the time of Tan’s announcement, Continuity still had $500 million in capital left to invest. It caught many prominent alumni off-guard, too, with at least ten startups expressing in a letter to YC that they were “surprised and deeply disappointed” by a decision that impacted the composition of their boards. Signatories included the founders of Brex, Deel, Rappi, Zepto, Convoy, and Monzo. Though undoubtedly a blow to Hariharan and her team, it also presented an opportunity. “I had assumed I wasn’t going to take anyone with me from YC, which is why I’d started conversations with Lucas [Fox] ahead of time,” Hariharan said of the recently departed Brex employee. “Now, I could also get Nic [Dardenne] and Tiffany [Kosolcharoen] from day one, which meant there were many steps I could eliminate, and we could spring into action very quickly.” By September 2023, seven months after Continuity’s closure, Avra Capital ran its first batch.

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The Avra academy

Almost exactly a year after Avra launched its program, welcoming eleven companies into its cohort, it is wrapping up its third batch. In the intervening 12 months, Avra is reportedly honing in on $350 million in capital, according to TechCrunch (Hariharan declined to comment on the matter). Andrew Davis, Managing Partner of Socium Ventures, shared his rationale for backing Avra’s debut vehicle: The easiest way to gain conviction in Anu’s track record was by seeing how many of the founders and partners she worked with chose to be investors in [Avra]. I have partnered with Anu for many years, and she is one of the most impactful and ethical investors I’ve ever worked with. We couldn’t say ‘yes’ fast enough when she asked us. As well as winning over limited partners like Davis, Avra has also honed its curriculum, built intriguing in-house software, and impressed some of the world’s most coveted growth-stage founders. Entrants include European OpenAI challenger Mistral, creative platform Runway ML, GPU orchestration system Foundry, gaming device Backbone, and many others. In devising Avra, Hariharan chose to build around a few key pillars – some inspired by YC Continuity, others in direct opposition: 1 Open to all. Since Avra is not part of an existing

offerings. The idea is that investment opportunities will naturally follow. 5 Personalized curriculum. Though growth companies

face the same set of challenges – scaling executive teams and maintaining high throughput – they do not all experience them at the same time. Avra tries to ensure its sessions directly attack founders’ most pressing problems, as well as prepare them for the future.

6 No strings attached. Admittance to the program is not

predicated on Avra investing, either implicitly or explicitly. Founders understand that Avra monetizes as a venture firm but are not pressured to solicit them for future rounds. Hariharan’s team believes it will earn the opportunity by delivering value, not by making demands.

These principles have guided the creation of the Avra apparatus, a machine that ingests thousands of startups but serves a select few. It is neither the slow, precious, boutique venture capital of the traditionalists nor does it adhere to Y Combinator’s industrialized model. It is something new, something in between – a processed, productized approach to small-batch brewing. Before exploring its curriculum, it’s important to understand how it sits within Avra’s broader structure and sequencing. In total, its methodology is comprised of 8 critical steps:

platform, it is free to accept any business it chooses without having to give preferential treatment to YC alumni. Places are given to the growth-stage firms Avra considers most promising.

2 Founder taught. Like YC Growth, Avra’s programs are

taught by expert practitioners, typically tenured CEOs or VPs with domain expertise. These people have gone through the same challenges as Avra’s students and can speak with experience and authority.

3 Off-the-record. Many venture firms produce first-rate

content for founders. However, when this information features advice from other entrepreneurs, it is inherently “on-the-record.” By keeping all of Avra’s sessions confidential, instructors are able to speak with greater vulnerability, specificity, and candor.

4 Education-first. Avra sees itself as an educational

offering first and a fund second. This is more than just marketing. The majority of the team’s time and focus is spent on improving its programming and associated

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The Avra Playbook. Source: The Generalist

Step 1: Data-driven sourcing

Avra scans tens of thousands of startups around the world through a bespoke early-detection system devised by Tiffany Kosolcharoen. Though it has a similar goal to the product Kosolocharoen built at YC Continuity – identifying breakout startups – it is being architected in a new technological era. “We get to reimagine it in the age of AI,” Kosolcharoen said. “The stack is being reinvented.” The early-detection system tracks approximately 50,000 global startups between pre-seed and Series A, excluding Chinese businesses and those in sectors Avra feels unsuited to advise. Though the fund is generalist in approach, it steers clear of a few highly technical, specialized pockets like biotech.

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Kosolcharoen and the broader team are tight-lipped about how exactly the system works but did share some of its key principles and a few example data sources. “There’s this large alternative data industry where hedge funds spend millions of dollars a year to acquire data sets. Through my past experiences, we’ve learned how to do it differently where we’re not spending that amount of money. We’re really looking at which metrics are leading versus lagging in breakout businesses,” Kosolcharoen explained. “For example, revenue might be a lagging indicator because it’s not necessarily the first metric that helps you identify a breakout business. The same is true of job openings – only after a company achieves a certain round of funding are they able to open up new positions.” So, what data sources are actually leading? Lucas Fox highlighted the importance of tracking Github repositories and stars, Twitter trends, and engagement via platforms like

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the new companies or entrepreneurs they follow. It also incorporates app traffic, web traffic, Hacker News upvotes, backlinks growth, and consumer credit card data. The system integrates qualitative signals, too, assessing the perceived quality of a founding team and the caliber of the company’s known cap table. In total, it tracks more than 50 custom sources to develop a sense of the current market. Through this process, Avra filters 50,000 startups to a shortlist of a few hundred that it continuously monitors. Further screening relies on manual intervention and nuanced judgment. Kosolcharoen creates “competitive sets” for different industries as part of this process. The idea here is to parse the dynamics within a certain industry to allow for cleaner comparisons between players. “It’s a really controversial, contentious topic because every single person at a company defines their competitive set differently,” Kosolcharoen noted. “It’s about identifying the peer sets today and then going through the game theory to see who might be in that peer set in the future.” The ultimate goal is to use this information to pick potential market winners. “There’s often a human angle to it, some product strategy, to identifying a category leader. You need to figure out which companies might converge onto each other,” Kosolcharoen clarified. “That’s a challenge if you anchor only on alternative data. The product roadmap and product strategy of a company doesn’t exist in a data format. You need a combination of looking at the data and the strategy to identify which companies may be inflecting among their peer set.” For example, an analysis of the neobanking space would not only compare Nubank, Revolut, Chime, Monzo, and dozens of other consumer offerings. It would have highlighted the potential for neobrokers like Robinhood and Public to make a play for the space, for B2B offerings like Mercury and Brex to try and win over consumers, for rent rewards-focused cards like Bilt to extend outward, and for stablecoin-based products like DolarApp to win with new rails. According to attendees of Avra's program, Kosolcharoen has a gift for this process. “She’s extremely talented at understanding business models,” Joseph Nelson, CEO of Roboflow, said. “When you have tactical questions around positioning, or what’s going on in your space, she can not only talk about it in terms of what makes sense strategically but also what’s playing out in the sector and how you should think about it as a result.”

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Looking at the 37 companies that have attended the program so far, it’s evident that Avra’s system has identified nonobvious candidates alongside some of the buzzy names previously mentioned. Anu Hariharan cited Clerk.dev as an example of Avra’s quantitative sourcing at work. Its system flagged the user management platform’s spiking sign-ups and encouraged Avra to reach out. In its second batch, Hariharan estimates that Kosolcharoen’s system helped select approximately 60% of the companies. Avra has also invited companies headquartered in Mexico, the United Kingdom, Saudi Arabia, Singapore, France, and Sweden – not entrepreneurial backwaters, but some way behind the USA. Before it gets to the invitation stage, Avra conducts further filtering. It cannot reasonably meet with hundreds of companies; instead, it watches them over time and looks for inflection points followed by consistent growth. “We do week-over-week monitoring. That’s how we know which ones are taking off,” Hariharan said. “The key is to measure it dynamically. Pretty easily, you get to a top 50 because not everyone is growing week-over-week.” Finally, Avra does external diligence to cut its top 50 down to 20 finalists. It conducts further research, speaks to customers, assesses the logos they’ve succeeded in signing up, and asks its community of founders for comment. “Our alums often say, ‘Talk to these people, don’t talk to those ones.’ They help us narrow down the list and also add founders we might have missed,’” Hariharan said. “They’ll say, ‘Hey, this company might not be on your radar because they just raised a seed and haven’t announced it, but they need to be on your list.’” These referrals are a critical part of Avra’s sourcing process. Founders are often excellent judges of talent and early adopters of new, disruptive technologies. According to Nic Dardenne, Avra is already benefiting from this process. “For our second batch, we were able to get 2030 recommendations from founders that went through the first batch or had previous relationships with,” he said. Hariharan noted that Anyscale (Avra Batch 2), an AI compute platform, had been referred by RunwayML’s CEO, Cris Valenzuela (Avra Batch 1). Similarly, Clair (Avra Batch 2), the provider of earned wage access solutions, came thanks to a recommendation from Plaid’s Zach Perret (YC Growth). “Clair actually hadn’t come up on our radar because they were just

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breaking out,” Hariharan said. “Zach said that we should really talk to them.” Step 2: One-on-one evaluations

they know everything. It won’t work for us, and over the long term, we have learned it does not work well for the company.” Avra looks for CEOs that understand their strengths and weaknesses.

Once Avra has identified 20 finalists, it contacts them for a meeting. Before getting to the meetings themselves and what the fund is looking for, it’s worth highlighting an advantage Avra has in this outreach compared to traditional venture firms.

Is it difficult to gauge self-awareness? Avra seems to find it straightforward, asking a series of questions that force introspection. A few examples:

Hot companies are constantly warding off investors; garlic, crucifix, and terse email responses at the ready. Any startup the market sees as a potential breakout receives a steady drip of inbound interest, requests for casual coffee chats, and suggestions of pre-emptive financing. Though the first such offers may be flattering, they quickly become distracting, which is why so many CEOs shut them down with a simple: “heads down building, will circle back when we raise next.”

What are three things you’re good at? What are three things you suck at?

Because Avra offers a specific, differentiated product, it is able to sidestep this tripwire. When a member of the investment team reaches out to a startup CEO, it is not asking to invest; it is offering something of value. Especially when this pitch comes via a founder who enjoyed the program, it’s a powerful sell. During its meetings with founders, Avra seeks to better understand the stage of the company and the capabilities of the founder. Three characteristics are particularly important: 1 Revenue threshold. Avra’s program is explicitly

designed for growth-stage companies. If a company hasn’t achieved meaningful revenue, it may be better for them to wait for a later batch. “If you haven’t gotten to $2 million in annual revenue, it doesn’t make sense to do the program because it is not a good use of their time,” Hariharan said.

2 Scaling speed. As well as surpassing a certain

threshold, Avra also looks to ensure a startup is growing rapidly. Much of Avra’s program focuses on building large, performant teams at hyper-speed, something a more modestly growing company may not need. “If you’re not scaling really fast in terms of revenue growth, you shouldnt be scaling your team,” Hariharan added.

3 A self-aware CEO. “I’ve had the privilege of working

with a lot of really good founders, and they’re very selfaware,” Hariharan explained. “It’s almost a signal we’re testing for because we don’t want founders who feel like

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What’s energizing about your job? What’s draining?

What are the strengths of your leadership team? How well do you think you’ve hired? These questions, and others like them, provide a window into how founders have solved problems and their current assessment of the business. Avra can’t invite every founder it meets with, cutting its 20 finalists down to a 10-12 company batch. So far, almost every company Hariharan has invited has accepted despite the commitment it requires. “The take-up is very high,” Hariharan said. According to Avra’s founder, only one company chose not to attend Batch 1 for timing reasons. Step 3: Kick-off retreat

To create an environment in which founders feel comfortable sharing their challenges and failures, Avra kicks off each batch with an in-person retreat in Santa Rosa, California. This is a time for attendees to get to know one another and build context on each other’s businesses. “It’s exceptionally helpful in setting the stage,” Roboflow’s Nelson said. “People share what’s working and not working inside their companies.” Vojta Drmota, CEO of Momence, shared a similar opinion: “You get to know the other founders on a personal level. There is no substitute for understanding who founders are and learning about their journey. That bond is really important for the rest of the program.” Avra works to build rapport through structured exercises. “It feels kind of like a summer-camp-manufactured-fun kind of vibe,” Joseph Nelson said. “But it actually kind of works and makes you feel more relaxed with your peers. It establishes trust and candor amongst people in the program.” Much of the retreat’s value occurs outside these teambuilding activities. “A big piece of it is just bringing people together,” Nic Dardenne explained. “It gives them a space 18

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away from their companies, away from their day-today, away from their laptop. It’s just free time to be able to connect.” Step 4: Classes

The reason Avra invests in creating rapport between batchmates is because it wants its classes to be discussion groups, not lectures. “A lot of the value comes from founders sharing their problems, not just from the instructors,” Nic Dardenne remarked. “You need it not to be a one-to-many lecture. People have to feel comfortable sharing and being more vulnerable.” Avra’s core curriculum is composed of 7 classes. Hariharan has asked that we not name the instructors so that we can share their takeaways while respecting the off-therecord nature of the sessions. These are Avra’s classes, in sequence: 1 Executive hiring and management (taught by two CEOs) 2 Mission, strategy, and metrics (taught by two CEOs) 3 Leading leaders (taught by public market CEO) 4 Operating cadence (taught by a CEO) 5 Scaling engineering (taught by two CTOs) 6 Scaling people management (taught by a CEO and

former VP of People)

7 Financial Planning and fundraising (taught by a CFO)

Before each session, students are tasked with “pre-reading,” which usually takes a couple of hours to consume. They may also be prompted to reflect on the topic and tell the Avra team what they’re particularly keen to learn about, creating a more tailored program. Lucas Fox gave an example of how this works. “Ahead of our ‘Leading leaders’ session in Batch 2, we spent five minutes with each founder ahead of time really understanding the number one bottlenecks each of them had as it relates to people management. Out of 12 CEOs, we got 12 pressing problems. And then, on the call with the instructor, we just went one by one, asking, ‘How would you tackle this? How would you think about this?’ It’s very tactical. It’s not a general talk.” The sessions themselves last approximately 90 minutes. Hariharan plays the role of interlocutor for instructors, prompting them to talk about certain experiences, share certain frameworks, or respond to questions. Her expertise S T R I C T LY C O N F I D E N T I A L

is obvious in this role. It’s clear not only that she knows the stories of the instructors’ companies intimately, able to perfectly poke and prod, but that she also understands what is likely to be most valuable to growth-stage startups. As teachers share their experiences, students frequently chime in with questions or comments of their own. Magical moments occur when multiple CEOs – both those in the program and those teaching it – weigh in on a given subject, explaining how their company handles executive compensation or engineering structure. Paul Copplestone, CEO of Supabase, highlighted the value of the discussions. “It’s super useful. And Anu is very good at prodding the instructors further. ‘What were the mistakes you made at this stage? Who did you hire? How many hours did you spend with executive recruits? What was your process?’ Anu’s constantly pulling them back to our stage – and maybe one step ahead. These topics are pretty timeless. There are all sorts of little tricks that founders have learned over the years. This is a way for them to pass that knowledge along.” For RunwayML’s Cris Valenzuela, the value of the sessions was less in picking up specific tips and more in hearing the thinking process of exceptional CEOs. “I’m less a fan of instructions and recipes and rules that you can follow,” he said. “I’m more interested in intuition and how people make decisions. You can learn a lot by hearing how successful companies have been built and the decisions people took along the way. That’s the exposure I wanted. It wasn’t about getting something particular out of it, more of a way of thinking about how to tackle specific problems.” Going through the experience together is another critical part of its value. “The reason the CEO job feels so lonely is because you’re grappling with things you’ve never dealt with before,” Hex founder Barry McCardel explained. “One of the few salves for it is knowing that the problems you’re facing are very common. When you go through a program like this, you get to talk to folks who are a few phases ahead and went through the same things you’re going through. You get to talk to other founders who have the same thoughts as you do. And they reaffirm for you that, yes, it is hard. And no, you’re not an idiot for struggling with it. It’s really helpful. It gets you out of your head and lets you zero in on the task at hand.” Step 5: Office hours

In tandem with classes, Avra offers weekly office hours.

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These are an opportunity for founders to reflect on recent sessions and talk through their particular problems in greater detail. “They’re super useful,” Paul Copplestone said, citing their impact on leveling up Supabase’s financials as part of Avra’s push for the company to create a “mini S-1” (more in a moment). “The mini S-1 project makes you think a lot and forces you to ask a lot of questions. Without the office hours, I would have been floundering a bit, especially around knowing how to write up our financials. The Avra team literally built spreadsheets for us, which I now use for our investors.” Momence CEO Vojta Drmota also found the added attention of office hours valuable. “In between sessions we would meet with Anu and her team. It supplemented the sessions very well because it was more pointed toward where Momence is now and what we need to focus on.” For Avra as an investor, office hours are another chance to diligence companies close up. Founders openly talk about their thorniest problems and discuss how they’re thinking about solving them. Avra then gets to observe how quickly and effectively they test different solutions and land on the correct answer. Though most growth VCs get to know potential investments over a long period of time (at least six months and usually a year) to create a longitudinal view of their progress, Avra gets to witness it up close and unvarnished. Hariharan highlighted how valuable it is to see founders address problems in real time. “How fast you move is very important. How long is a founder sitting on a certain decision? Do they have tight feedback loops, and are they course-correcting quickly? What frameworks are they using? Do they get stuck by brick walls, or do they know how to run through them?” Step 6: Mini S-1

Avra’s batch culminates with an exercise: writing a “mini” S-1 filing. The goal is for founders to understand how their business fits into the broader corporate landscape, learn how public market investors value comparable companies, reflect on the core drivers of their current success, and sketch a blueprint for life as a public business. Vojta Drmota outlined the process and its value. “It teaches you to present your business in a structured fashion. That’s something you don’t do as a private company on a regular basis. You write investor updates, but this is a much more detailed format. S T R I C T LY C O N F I D E N T I A L

That’s very helpful, in and of itself,” he said. “Another key part of it is that in the S-1, you have to explain to an investor the $10 billion, $50 billion, or $100 billion outcome. You have to indicate where the company can go to impress upon investors that it’s a worthy investment. That’s not something you really think about as a founder. You think about, ‘How do I get to the $15 million revenue mark? How do I get to the $25 million mark?’ You rarely think about how you get to $5 billion or $10 billion.” Thinking in those terms forces a level of bottom-up analysis that many startups don’t prioritize early in their lives. “You have to articulate what the best case scenario for your TAM is, what your market share has to look like, and what ACVs have to look like,” Drmota said. “It forces you to think not just about your mission but how it can be materialized.” Founders rely on help from Avra and feedback from their batchmates to craft their S-1, which they eventually present in front of prominent public market investors. “It’s definitely an interesting process,” Cris Valenzuela said. “You learn a lot just by doing it, but you also get a lot because you speak with other people about it and get feedback. It helps you understand the future things you should be thinking about. I’d never done it before.” Anu Hariharan consistently and earnestly emphasizes that office hours and the mini S-1 exercise are done to serve founders. There is no doubting the sincerity of that suggestion. The pragmatists among you cannot help but notice the advantages these exercises grant Avra the investor. From that vantage, the S-1 exercise asks founders to diligence themselves, presenting their findings and future growth for review. In essence, they are creating a pitch – stuffed with detail, risks, and opportunities. This exercise would not work if founders didn’t find it valuable; a happy byproduct is that it doubles as investment research. Step 7: Private wiki

If a YC alum needs a question answered, there’s a good chance they’ll post on Bookface. That’s the name for the accelerator’s private site featuring a discussion forum, investor ratings, a library of resources, and various perks. Avra is building its own version of that resource, designed for growth-stage entrepreneurs. For now, the private wiki is barebones but already intriguing. It features a directory of the 42 founders who have attended Avra’s program, access

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to a private off-the-record podcast, and a wiki that documents key lessons from across the curriculum. Visit the page for “Leading leaders,” for example, and you’ll find wellstructured notes gleaned from the associated session. Over time, Avra plans to add to these pages, creating a repository of high-quality information that helps founders during the program and beyond.

relevant fields. As funding ebbs and flows and disruptive technologies like AI change the game on the field, this ongoing education is extremely valuable.

It’s exciting to envision what form this might take. As well as incorporating expertise from multiple CEOs over time in a given page, Avra could also collect collateral from different entrepreneurs. Sometimes, simply seeing how a founder lays out their hiring process on the page, or builds their board deck, can make a tangible difference. Roboflow’s Nelson hopes Avra facilitates more of this resource sharing. “I think there are probably ways to grease the wheels and make sharing resources more commonplace. For example, making companies more comfortable walking through recent board decks and trading ideas. You can only do that when you have a close relationship.”

In the course of a cumulative 12 hours, I learned how some of the world’s best CEOs manage their recruiting, financials, engineering teams, and fundraises. I heard of common mistakes, near-death experiences, and miraculous turnarounds.

As the trusted connection between its instructors and students, Avra is positioned to act as the hub for this information. In time, growth-stage founders may want to join Hariharan’s community as much to access this library as to attend its course. Step 8: Alumni sessions

Though Avra’s program culminates with the mini S-1 exercise, the firm’s relationship with founders continues beyond it. As well as continually adding new resources to its wiki, Avra holds alumni sessions and an off-therecord podcast. There is no real difference between these two products. Both feature Hariharan holding a conversation with a prominent founder, operator, or technologist, using her expert prodding to deftly direct the discussion. Past sessions have given founders an opportunity to learn about AI from a long-time expert, hear about a remarkable public market turnaround, and discover how an external CEO rescued a flagging unicorn from collapse. The idea of the podcast is to inspire founders during their most difficult times. Alumni sessions are an effective way for Avra to augment founders’ education and address transient issues. For example, had Avra existed during the Silicon Valley Bank catastrophe, it would have been well-positioned to put together a rapid response session, pulling in experts from S T R I C T LY C O N F I D E N T I A L

Class is in session

The hours I spent with Avra’s curriculum were among my highest-leverage of the year.

All of which is why I’m extremely excited that Avra has allowed The Generalist to share takeaways from the program. To be clear, these are just the tip of the iceberg. Each session is packed with fascinating insights – some obvious in their value, others more subtle. When Hariharan pitches the program to founders, she tells them they will receive direction in three areas: 1 Executive hiring and management 2 Shipping fast as you scale 3 Execution and clarity of thought

Rather than walk through all seven sessions, we’ve distilled impactful pieces of advice from the entire curriculum that fit those categories. Naturally, to respect the confidentiality of the instructors, we’ve kept them anonymous and stayed clear of identifying information. We’ve highlighted universal takeaways that stand alone and that we believe will be of greatest use to other founders. Focus 1: Executive hiring and management

To scale your company, you must learn to hire exceptional people with capabilities that surpass your own in at least one dimension. Though founders are used to pinch-hitting across functions in a startup’s early days, winning in the growth phase necessitates finding and converting executives who can take your company to the next step.

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1 Executive hiring success rate. A surprisingly large

number of executive hires do not work out. Hex founder Barry McCardel cited this as particularly valuable information. “People will tell you that a good success rate for leadership hires is 60-70%. In reality, it’s closer to 50% for most companies, which is insane when you think about it. Hearing from other CEOs who are further along in their journey [was really helpful.]” Great executives surpass these levels. One CEO said that their last 15 executive hires had all worked out, an “exceptional” record.

2 Don’t skip the references. It’s easy to skip out on

referring executive hires earlier in your company’s life. Often, you might think you have enough information to make the call yourself. Don’t take this shortcut. One instructor said that 30% of the team references revealed a piece of critical information about a recruit. When you conduct references, ask the reference to score the person out of 10. Anything below a ‘9’ should be considered a poor score.

3 Take a “breadth-first” approach to the executive

search. A common cause of a failed hire is not knowing the profile of the person you’re recruiting for. To prevent that from happening, conduct a “breadth-first” search in which you speak to different “flavors” of the role you’re hiring for. For example, if you’re recruiting a CFO, talk to one with more of an accounting background, one that’s more FP&A oriented, and one that focuses on strategic finance to see which feels like the best fit. When you find the right person, be aggressive in winning them. “Elite founders don’t lose candidates,” was one CEO’s mantra.

4 Invest heavily in executive onboarding. When you

succeed in hiring an executive, give them the tools to succeed. Align on the expectations for the role, and have them devise a plan for their first 30, 60, 90 days. (This is a place where you should lean on their functional expertise.) For the first 30-60 days, encourage them to spend as much time as possible simply learning about the organization rather than managing direct reports or producing work. For example, one incoming CEO conducted 80 one-on-ones and 20 group meetings before officially taking the reins. This is time well spent.

when you notice their salary lags behind their impact. This will prevent them from feeling undervalued and looking for a new role. Additionally, one CEO recommends conducting stock refresher grants around the 2.5-year mark of an employee’s tenure as many consider their next move after about three years. Focus 2: Shipping fast as you scale

Founders often think their organization will accelerate as headcount increases. After all, can’t you achieve more with more people? It’s more common for the opposite to occur, at least in the short term. As your company scales, old processes break, the quality of new hires degrades, and coordination costs grow. Shipping fast as you scale requires an uncompromising mindset, intense work ethic, and sound strategy. 1 Don’t accept “CEO in a box” trade-offs. Internal

leaders will often come to you with either/or decisions: you can either have a product built fast or with quality; which do you want? One executive calls these “CEO in a box” trade-offs that should not be accepted. Why can’t a product be delivered quickly and with exceptional quality? It is almost always possible to avoid these false compromises.

2 When troubleshooting, look for anecdotal evidence,

not data. When a part of the organization is not working, it’s more useful to dig into transcripts or Slack messages than review high-level numbers. If the support team is lagging, read the last 25 tickets. If sales is underperforming, read the last 25 Gong recordings. You’ll spot patterns and get much deeper context than a dashboard can provide.

3 Commit to crazy. While attending an accelerator like

YC, founders are pushed to their limits and operate at a frenzied pace. According to one CEO, when the program ends, most people revert to a much slower cadence. To build a legendary business, you cannot allow yourself to do this. Instead, you should be part of the few “crazy motherfuckers” that maintain that relentless speed. Working 20% more doesn’t yield a 20% productivity increase, according to this CEO; it delivers “way, way more.”

5 Proactively give raises to retain talent. Employees

who scale alongside a startup often drastically increase their importance in a short amount of time. To avoid losing these people, give “out of band” pay increases

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4 Go slow to go fast. To build engineering teams that ship

quickly, spend time upfront on two key areas: data modeling and core technology decisions. Both of these are difficult to change down the line, so think it through before committing. On a related note, consider introducing code reviews and tests from day one or close to it. Both will save you time in the long run and ensure you have strong engineering foundations.

5 Break your engineering team into pods. As your

company scales, you’ll need to manage an increasing number of engineers. Splitting people into arbitrary teams can drastically increase communication and coordination costs, slowing down shipping. One CTO outlines the approach his company uses, organizing itself into small 8-10 person “pods.” Pods are composed of 5-7 engineers, a PM, a designer, and a data scientist. Pods are given the context and resources they need to achieve their goals but are empowered to set their own strategy and to act as “small startups.”

Focus 3: Execution and clarity of thought

In preparation for your Series B, take the time to look toward the future and build the systems you need to achieve your ultimate goals. Startups are constantly faced with urgent issues that require attention. You must proactively make time for non-urgent but still important subjects. In particular, make the effort to define your metrics, hone your messaging, and prepare for future raises. Separate input and output metrics. Companies are used to focusing on “output” metrics like revenue or monthly active users (MAUs). Though this information is useful, especially for investors, it’s insufficiently actionable. What do you have to do exactly to grow MAUs? “Input” metrics are KPIs that help drive your output metrics and are more directly within your control. For example, to increase revenue as a food delivery company, you might set input metrics of order frequency and customer retention, as these could make an impact on your topline. Picking the right input metrics will require data analysis and deep consideration, but once you identify them, it’s much easier to direct your team’s efforts effectively. Repeat your message consistently and frequently. Creating alignment across the organization requires you to restate your company’s mission, metrics, and strategy much more than you might expect. At least every week, you should re-communicate this to the company, using S T R I C T LY C O N F I D E N T I A L

consistent language. Though it may seem like overkill, it’s critical to maintaining a common goal, refocusing different teams, and getting new hires up to speed. Financial planning by confidence interval. As your company matures, building out a strategic financial department becomes essential. You will need a Head of Finance and, eventually, a CFO who can help you set realistic projections and plan for the future. Though setting goals often begins top-down, with a CEO outlining their ambitions, it should gradually become more bottom-up as the team scales and your processes become more predictable. Nevertheless, making perfect projections can be difficult for an organization that develops rapidly. One strategy is to plan for whatever period you have 70% confidence you can accurately forecast. This might be three months, six months, or a year. While this shouldn’t replace your annual planning, it ensures your forecasts don’t drift too out of line. Lay the groundwork with investors. Growth-stage investors are writing larger checks, typically in the $20100 million range. As a result, their process is longer and more detailed. To ensure you fundraise from a position of strength, identify 5-10 investors you believe would be suited to lead your next round and begin building relationships with them 6-12 months ahead of when you plan to raise. This gives VCs the opportunity to get to know you better, learn more about your model and market, and arrive to the fundraise with a prepared mind. It also allows you to vet potential partners. Running a tight fundraise. If poorly managed, raising capital can take months or longer. You should drive investors to follow a 1-4 week diligence process. For that to happen, you must arrive prepared and equipped with a well-stocked data room. Once the process has begun, you should focus your attention on “high-signal investors” – namely, those that actually seem interested in your business. A good rule of thumb: “An interested investor tries to speed you up rather than slow you down.” When possible, use the momentum of other VCs to drive peers through the process. Aberrant venture

Venture capital, all of its theater and competition, can be condensed into six essential tasks:

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1 Sourcing. To invest in a legendary company, you must

6 Exiting. To realize a return on an investment, VCs have

2 Assessing. Once you’ve identified a potential

Not only do these six tasks neatly summarize the work of a venture capitalist, but they also describe the sequence in which this style of investing occurs. Though there’s frequent overlap between them, each more or less operates as a distinct step in the process: you find a business, evaluate it, win it, “work” it, and sell it. It’s chronological and sequential.

find it first. Sourcing is the art of discovering as many high-quality opportunities as possible, ideally before your rivals. investment, you must spend time diligencing it. At the growth stage, this often occurs over months or years of conversations and formal research.

3 Winning. Just because you have conviction in a startup

does not mean you get to invest in it. Venture capitalists have to convince founders to let them buy shares, often over competitors.

4 Investing. Though usually winning a deal results in an

investment being made, they are theoretically distinct steps. Because of Avra’s model, and its quirks, it’s worth separating them.

5 Supporting. Not all VC firms want to help their portfolio

companies, with some believing it to be a folly. Most do, however, assist with hiring, business development, future financing, and much more. This is the “adding value” phase that VCs market to the point of parody.

to exit their position at some point. This may occur as a company enters the public markets, via an M&A event, or through secondary sales.

One of the most interesting aspects of Avra’s model is that it rearranges these steps to its own benefit. Though Avra starts by sourcing companies, it follows that stage by assessing, winning, and supporting a startup all at the same time. Its program compresses these three steps into one: Avra assesses a company as it adds value and, in doing so, preemptively wins the right to invest. Avra follows this process with all of its companies, including many it will not invest in. Only later on does it actually circle back and deploy capital.

In good order: How Avra reorders venture capital’s traditional sequencing. Source: The Generalist

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It’s a meaningful twist on the venture model. Though investors and founders spend time getting to know one another and learning about each other’s businesses, there’s an unavoidable leap of faith made when entering into a partnership. A blustering dealmaker may spend months telling a CEO how they’ll win them customers, drive candidates to their doors, and broker introductions, only to disappear once the ink has dried. Another financier may extoll the virtues of an expansive in-house team and sophisticated software stack, open only to portfolio companies, and leave the entrepreneur with ineffectual help and vaporware. Because Avra proactively frontloads its value-add, founders don’t have to worry about a bait-and-switch. Hariharan’s firm does not tell you how it can help; it shows you in vivid detail. When it comes to partnering, the leap of faith has been shortened into a puddle jump. Several of the founders we spoke with expressed their interest in taking money from Avra despite the fact they were not actively fundraising. This is especially notable given that Hariharan’s firm works with many of the ecosystem’s hottest startups who have an abundance of funding options. “If we end up doing a round, I’ll definitely reach out to them,” Supabase’s Paul Copplestone said. “The most helpful and best investor in terms of helpfulness is definitely YC. I’d put Avra right next to them,” he added. “We’re not in a fundraising situation right now, so it’s hard to say, but I don’t see a reason why we wouldn’t reach out to them,” said Vojta Drmota. “I think it would be a strong yes.” No venture investor can win every deal they want, of course, and though Avra has unique weapons, it also has weaknesses. “There are upsides and downsides of a new fund,” Joseph Nelson said. “One of the downsides is that a lot of the value for a fund is driving market awareness, whether that’s companies or candidates. That’s something I’m sure Avra is aware of. It’s just like a startup – you just have to offer to ensure you win a customer’s business.” The early indications suggest that Avra’s product is doing a good job of winning founders’ business. So far, Hariharan has backed two companies, Zepto and Supabase, which did circle back to Avra a few months after our interview. Interestingly, Zepto is not a graduate of Avra’s program but a breakout business that YC Continuity previously backed. The fact that Avra participated in the grocery delivery company’s

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$665 million Series F round illustrates its ability to be flexible and pragmatic, investing in the best opportunities for which it has a prepared mind. It also hints at a remaining opportunity Hariharan and her team intend to address: pre-IPO businesses. Just as growthstage founders need dedicated help, Avra is convinced that CEOs heading for the public markets could benefit from tailored tutelage. “The culmination of a great journey is becoming a public company,” Lucas Fox said. “There’s a reason the vast majority of the Fortune 500 is public – it comes with operational rigor, and there’s a lot of beauty and elegance in being a high-performing public business. We want to be able to partner with founders from the moment they start scaling through to the public markets.” It would be a shrewd addition. For even exceptional startup founders, entering the public markets is a learning moment. It requires education and preparation, as well as the embrace of new rules and norms. Fox outlined what this program might look like: “We’ll invite companies that are 1-2 years from being public, and invite them to do a smaller program, probably on the weekends. We have alumni from the program that have already taken their companies public who can teach. We’ll separate it into certain modules, just like the current Avra program designed to help founders avoid common mistakes. It might talk about how to pick the right investment bank, structure your audited financials, or tell your story.” By assisting founders at this stage, Avra would once again get a front-row seat to analyze them and could win the opportunity to invest ahead of a public debut. It’s an intriguing position in the capital stack, as there’s relatively little risk, often notable upside, and a much shorter path to liquidity. Crucially, it also strengthens Avra’s existing machine. At the moment, much of the fund’s success depends on its goodwill with talented founders willing to teach its sessions. Without these exceptional instructors, it might struggle to attract high-quality growth-stage entrepreneurs to attend its program. Though Hariharan can relay stories and frameworks second-hand, it is more powerful for CEOs to learn directly from one another. By introducing a pre-IPO program, Avra

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could expressly “reward” those who teach its growth-stage program. Though these are not purely transactional relationships, having a tangible way of returning the favor and deepening the connection between Avra and this critical stakeholder fortifies its approach. “It would tie into the whole ecosystem,” Fox said. “We want to find a way to add value to our teachers as well. We do that one-off right now by introducing them to key people, but we want a systematic playbook to funnel these guests into so that they feel like they’re part of the program, too.” Running a high-growth startup is a job for which there is no real training. It might help if you’ve already built a career for yourself, but it can just as easily work against you. It’s a bonus if you can code, but certainly not a prerequisite. Have you finished your module on self-reliance? How about your symposium on irrational hubris and unhealthy tenacity? From which institution did you receive your Master’s in resourcefulness? Which PhD program granted your doctorate in pain tolerance?

SOURCE

To build a business is a lonely, bruising job; to do so while having your foot glued to the gas pedal ratchets up the stress and risk to the mix. Since the closure of YC Continuity, Avra has emerged as the only serious school for the tiny subset of people building rapidly scaling businesses. Its existence is a benefit to the startup ecosystem and an illustration of the innovation still possible in venture capital. Amongst predictions of a great culling in the asset class’s ranks, Avra shows that new funds are viable, and new approaches can – with enough originality and distinctive value – become increasingly essential. The secret may be to operate as little like a venture firm as possible. The Generalist’s work is provided for informational purposes only and should not be construed as legal, business, investment, or tax advice. You should always do your own research and consult advisors on these subjects. Our work may feature entities in which Generalist Capital, LLC or the author has invested.

Read the Original www.generalist.com/p/avra The Generalist, 3 October 2024. Reproduced in TOP Venture format for LP reference.

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AREA

Tue 13 Oct

Menlo Park

Joe Kauffman President & CFO, Deel

ARTICLE 3

SACRA · 5 NOV 2025 · JAN-ERIK ASPLUND

Alex Bouaziz, CEO of Deel, on Deel’s bundle-unbundle strategy

Image: Sacra

Background

Key points

We last covered Deel in early September at $1.15B/year growing 70% YoY. Since, in mid-October it announced its $300M Series E valuing it at $17.3B, led by Ribbit Capital, A16Z & Coatue.

– Out of the crowded market for global employment platforms circa 2020 (Remote, Oyster, Papaya Global), Deel emerged the winner through its rapid product expansion from international contractor payments (2019) to EOR (2020) to global payroll (2022), that simultaneously reduced churn & graduation off the platform, drove expansion in seats & revenue per seat and massively increased the scope of Deel’s TAM. “When we were starting up, the contractor product was the very first one. Our customers would eventually need an EOR provider, so they would churn out of Deel. And then eventually, when they were using our EOR product, they would need a payroll provider, so they would churn out of Deel. . . today, we're a full HR and payroll platform across every

On Monday, Deel announced that it had appointed ex-Credit Karma CEO & CFO Joe Kauffman as CFO, moving co-founder & CEO Alex Bouaziz’s father Philippe from CFO to CSO as it prepares to go public. To learn more, we spoke with Alex about the Series E, Deel’s push into the enterprise, and its timeline for IPO.

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single market.” – Deel’s global payroll push required investment in physical infrastructure—local entities & licenses, incountry legal/HR staff, and jurisdiction-specific compliance engines—taking on that operational & compliance responsibility for customers and creating a moat against competition that upstarts & rivals cannot replicate through code alone. "Compliance and infrastructure—licensing, for example, in different countries, the EOR model where we own licenses to be operating and stuff like that—in a world where you can build up a SaaS in Lovable in a couple minutes is probably the biggest moat a company can have. Whether it's their own infrastructure, licensing infrastructure, financial licensing infrastructure, that's the biggest moat that you can have as a business, and a lot of companies are going to start realizing that and double down on this for sure. – Its fastest growing customer segment, Deel’s approach to the enterprise (recent wins with FedEx, Databricks, Verizon) looks to bypass the decadelong Workday displacement cycle with its bundleunbundle strategy of selling any single product for any number of seats and expanding from there— with a 2026-7 IPO eyed to strengthen its positioning as enterprise-grade. "It's very hard for companies at the SMB level to be able to win [enterprise] businesses. And enterprise is actually our fastest-growing segment. I'm not even going to try to sell to an enterprise today a full-stack HR solution because it's going to take me years to get there. . . But on the payroll side, it's so fragmented, such a poor experience. On the EOR side, same thing, that we can really get into accounts that are at the enterprise level much quicker.” Interview

Congratulations on the Series E. Can you talk about why you raised, the timing, who's leading, who's involved, and the milestone moment?

Very excited about this. It's actually a pretty big milestone for us because, depending on what you consider the 2023 $50 million round—which is a little lower than the usual fundraising round—the last time we raised primary capital was in 2021 with the $425 million round. So it's the first time we've raised significant primary capital in quite a while, and we're very excited to have the amazing team at Ribbit Capital, with Andreessen Horowitz and Coatue co-leading S T R I C T LY C O N F I D E N T I A L

this round together. We have a bunch of other amazing investors following, like General Catalyst and Green Bay Ventures. What's super cool is I love the funds we're working with. Ribbit is a fund that—I don't know if you've ever talked to Micky [Malka] or Nick [Shalek]—I love them. I've been wanting to work with them for a very long time. So having them lead a growth round, which is something they don't usually do, is a strong testament to their belief in the company and where we are. And having our amazing investors like Coatue doubling down on the company, or Andreessen Horowitz, is a strong statement as well. So yeah, I'm very excited about this round. You guys are profitable. How do you think about fundraising, especially leading into a potential 2026, 2027 IPO?

We've been profitable for three years, so we've been generating cash for quite a bit. The way I look at it is I've been lucky enough in my life where I've always focused heavily on sustainable growth and profitability. So although we're growing really fast still, since our seed round, we came into our Series A having raised a $14 million seed round and having spent only $375k at the time. We've always been very anchored on how to grow sustainably and profitably. And what that triggered is we've always been in a situation where we considered that the round we had closed could technically be our last round ever. So we've always been quite thoughtful about how we do things. And what happens with that is I'm usually never in the market, so I'm never fundraising. Every single one of our rounds, due to that, actually happened through investors preempting their own, which is always flattering, of course. In this case, it's exactly what happened. Coatue and Ribbit did a bunch of due diligence for a while because they actually wanted to buy secondaries in the business. Coatue has been buying secondaries for all this time, actually. And the team at Ribbit was planning on doing the same, and it just came together where they were like, "Hey, what about us just doing a primary instead?" And yeah, we're very excited about it. From a pure use of funds perspective, we've been pretty active in the M&A market. We've done 13 acquisitions so far, and this is a trend we're going to keep going on. So resetting the valuation of the company is a great idea when you're about to bring on more businesses and go out to market. 28

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Second, we've been investing really heavily in our infrastructure. We're doing something that really hasn't been done before, which is building all payroll engines in every market and actually doing gross-to-net calculations and covering every single edge case of payroll in every single country across every single industry. That is a pretty big endeavor, and we've been able to, just in the last year, increase the amount of provisions that we have by almost 10x. Doing this over the next few years is going to be a significant undertaking, but it's just going to require so much investment that it's never a bad idea to have additional capital. And like every single company, we want to double down on AI, and some of those AI talents cost quite a bit of money. So capital is not a bad idea. When Deel was founded, it was highly competitive with Remote, Papaya Pay, Panther, Oyster, Ontop, and many others. It looked like it wasn’t a winner-take-all market and there would be many winners potentially. Why did Deel win in this highly competitive market?

We are very blessed to be in a very strong market where there was a lot of money funneled in. That just raised the bar for the quality and the talent that our customers expected. When we started working on Deel, as you know as a customer, we followed our users. We started with the contractor product, moved to the employer of record product, eventually moved to the global payroll product. And today, we're a full HR and payroll platform across every single market. We're really the only company from our space to have evolved with our customers. The way we've evolved with our customers has been very critical to our growth for obvious reasons. For example, when we were starting up, the contractor product was the very first one. Our customers would eventually need an EOR provider, so they would churn out of Deel. And then eventually, when they were using our EOR product, they would need a payroll provider, so they would churn out of Deel. Following the growth of our customers and following the product needs that they had has been one of the key parts of our growth. Beyond this, there's just a few things from a pure execution perspective. We've always been much more customercentric in terms of building fast for them and being very present in the relationship and top-down just doing our best for our customers. And again, it's not to say that other companies haven't, but we had a very strong emphasis on S T R I C T LY C O N F I D E N T I A L

that. The combination of all of this together, plus a good product, good timing, a lot of luck, and great executives in the business, is what helped us set ourselves apart. Now, I still think Oyster, for example, is a great business, and they're going to keep doing great. I don't really know what's in store for them, but I know that a lot of customers are very happy using their products as well. In this 2020 era, there were all these trends driving international hiring—remote work and COVID, whitecollar labor unrest, Black Lives Matter, the high cost of health care in the United States. Post-COVID, a lot of the companies that were very COVID-indexed decelerated, but Deel has continued to grow. What adjustments did you make to continue to grow post-COVID?

First of all, I don't mind demystifying that Deel's growth was very tied to COVID. A lot of the marketing we had and a lot of the interest we had was tied to COVID. But if you look at 2020, we were a tiny company, almost no revenue. So it's not like that much revenue was really tied to this. In 2020, hiring globally was already a thing. Companies already had offices abroad. Companies were already engaging with their workers. We made it easier for companies to be able to have global teams, but our initial customer base were people that already had global teammates. We just made it easier for them to be able to run payroll and manage all of them in one place. The second part is what I believe COVID really did for us— and in many ways, it did help us from a marketing standpoint at the time—is it made people realize that if everybody's working remote, giving a great experience to all of your employees, not just the ones in your HQ, mattered a lot. Suddenly everybody is at home. The person that's at home in Nigeria, in Peru, or in the U.S. is just exactly the same as your usual employees. When you have everybody in one place, in one headquarters, and just a couple employees here and there in a few other places, it's easier to favor the people that are all in the same place. But when everybody is in exactly the same situation, then you tend to want to give the same experience or at least a better experience to everyone. So that was actually one of the very strong tailwinds we got from this, which is heads of HR realized, "Hey, we're actually giving a subpar experience to some of those teammates. Let's actually fix that." Beyond this, we did grow into becoming the people platform for global teams. When people look at us today, even if there 29

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are some leftovers of, "Oh yeah, you guys are focused on remote workers," it's like every single company—you grow as a brand, so people need to eventually understand who you become as a business, and it takes time to anchor that in their mind when one thing worked out really well. We're starting to really be seen as the global HR and payroll platform for most companies, whether they're small businesses or enterprise. And that's the biggest tailwind for us—that now it doesn't really matter, remote or not remote. We'll just run payroll everywhere you have people. We'll just help you hire wherever you need, wherever they are. That is the very interesting and fun transition that we've been going through, which separates us from being a onetime or one or two product wonder that gets to great revenues into a potential generational business. Can you talk about Deel's vision for AI? Also, AI is enabling companies to build with smaller teams, and fundamentally Deel monetizes per employee. Do you see AI as a headwind or tailwind and why?

We've been working on AI products since OpenAI's APIs were available. As soon as we could build great things, we went for it straight away. There's a couple of things here that we did early that were very helpful for us. First of all, in 2022, we made a pretty big decision, which was to build our own database infrastructure, our own internal wiki. We love products like Notion and others, but if we're going to be the encyclopedia and have all of that knowledge in one place—given we have local people across payroll, employment, benefits, legal, etc., in every single market—we need to own the data structure itself so that we can actually control the quality of the data and be able to do reinforcement learning and all that. So that was one of the big things we did very early on, which really shaped us as a product. Today, we have 68,000+ edits and changes inside our own wiki weekly because compliance changes all the time in every single one of those countries. Being able to layer great models like OpenAI and others on top of this just gives a steep increase in customer experience and how things can work. Beyond that, there's so many things I'm excited about when it comes to bringing AI onto the platform. I don't know if you saw, we recently launched our AI Workforce Hub. Basically, what that stands for is, okay, if you go with the mindset that you're going to have agents that are going to be working for you—they're going to automate a lot of the tasks that are S T R I C T LY C O N F I D E N T I A L

maybe a bit more mundane—there's still a world where people will need to measure the performance of those agents. What better platform than the platform where you actually have all of your employees in one place to be able to assign different agents to them, the performance and monitoring of them, and even the performance and rating of those agents? One thing I was laughing about when we did our launch was I was telling some of our customers that were using the product and testing—one customer was actually bragging to me that she had so many agents that were built in-house and stuff like that. And my question to her is, "Have you ever fired an agent?" Keeping a tidy house into what you're actually using from that standpoint is really great. So we launched that with a few agents. We launched a bring-your-ownagents product, and we think this is going to be really great. Beyond that, as a business, as you can understand, we're a very operational business. We have people in every single country, every single jurisdiction: HR, legal, payroll, etc. There's just so much you can automate through this. The way I think about this is, if I take my team today, can I give them superpowers to be able to automate a lot of the work they're doing? If you take this and you combine it with payroll engines in every single country, we can really blow up from a gross margin perspective, but more importantly, from a customer experience perspective. Regarding your last question when it comes to headcount, not really. There will be just a lot more companies with a lot fewer people, which is fine by me. Because at the end of the day, every single significant industrial revolution led to different jobs being created. At the moment, what's happening is we have amazing marketplaces that are doing a lot of AI labeling. A lot of those AI labelers are actually being hired through Deel, and our embedded product and our white-label product are doing amazing in that market. So every cycle has different moments. It used to be crypto. Crypto is coming back, but we serve most crypto companies. Now it's looking like AI. And if you look at the number of AI businesses that we serve today, whether it's the Mistrals of the world or the Anthropics of the world, we're very proud of having them as customers and think there are going to be more businesses, maybe fewer people, but more of them. Can you talk about compliance as a headwind versus compliance as a tailwind? Customers buy you because you take the problem of compliance in local jurisdictions off their hands, but at the same time, what risk are you 30

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taking on? How do you think about your exposure to different things, especially these high-degree-ofdifficulty problems like EOR where there are a lot of ways to get tripped up?

Compliance and infrastructure—licensing, for example, in different countries, the EOR model where we own licenses to be operating and stuff like that—in a world where you can build up a SaaS in Lovable in a couple minutes is probably the biggest moat a company can have. Whether it's their own infrastructure, licensing infrastructure, financial licensing infrastructure, that's the biggest moat that you can have as a business, and a lot of companies are going to start realizing that and double down on this for sure. When it comes to the business itself—today, we have 19 different products including our HR product, our Engage products like performance reviews and learning, our Deel IT products like global equipment and managing IT, and our payroll products. Across all of those, generally, we've always had compliance at heart. It might sound silly, but what courses do you put in front of a German employee versus a French employee versus an American employee in California, for example? So when it comes to this, it's what really makes us unique in a way. Every single product we built, we have it with compliance in mind and compliance first. The fact that today we have more than 2,000+ people internally who are experts on payroll, legal, etc., really gives us a significant edge that most companies don't really have. The one product that you're looking at where you're actually getting at is our EOR product, where we're actually employing the person on your behalf when you don't have the infrastructure. And to be honest, we run a pretty tight ship there in terms of credit control, in terms of losses, in terms of taking a deposit and generally managing exits and helping companies and employees exit the correct way and doing it compliantly.

revenue distributed among the other product lines? Which are the fastest growing? How do you anticipate this revenue mix looks in three years? Five years?

The way we break down our products and our revenue, you obviously have fintech, which is a significant part of our business—25-30% of our business as well. We move more than $2 billion a month across every single currency you can think of. But more interestingly, we can see that the different products in our ecosystem have been really getting the appetite of our customers. Deel IT, for example, represents now almost 7% of our business. And it's grown double since the acquisition of Hofy and rebuilding the product in-house. We've gone from managing global equipment for our customers to all of the different products that you could be expecting from IT. Same thing for immigration. We started with acquiring a company that got my own O-1 visa at the time. Now, we help thousands of people get not only the O-1 and other US visas, but visas in about 100 countries, all in one solution. Our take is we don't want to force our product down your throat, which has been the standard go-to-market for a lot of companies in this business. We actually want to have what I like to call a very strong bundled-unbundled offering where you can come and just use us for U.S. payroll or for one person in that country or for your contractors or for our learning product. And then, technically, we'll be able to sync into whatever ecosystem you have, whether you're an HR leader or finance leader, so that you can actually enjoy the benefits of just one great product.

There's a lot on the line because, technically, we are in that specific case—while it's not in the other cases—the employer. But it's also our bread and butter. So we know how to do this, and we've been able to just get better and better over the years.

And look, over time, it's our job to build a relationship in a way where you're like, "Hey, you know what? I might actually give a run at that product." And we see it in the numbers. Our HR suite product, Deel Engage, which is a full performance learning suite, has grown more than 540% in the last year. Same thing—I was talking about the IT product, but same thing with U.S. expansion. It's something people don't realize, but our PEO business is giving the market a run for its money. It's really good. It's getting better by the day. And we're seeing so many customers looking at this and saying, "Hey, look, I know what Deel is from a service perspective."

You said contractor payroll is a $130 million per year business, EOR is $300 million per year, payroll is $150 million per year. That comes to around $580 million per year. How is the remaining $620 million per year in

Because remember, payroll is so commoditized that a lot of companies take their customers for granted. But because global payroll is so complicated, we always over-index on great service and being very close to our customers. Of

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course, we don't get it perfect all the time, but it's actually very hard. We actually overinvest in that because the global payroll side is so hard. When we come into the U.S. side and give the same service that we've always been giving on the global side, our customers look at it and say, "Wow, that's the type of service I actually want and I deserve across all of my stack," while, until we went into the U.S. market and brought that mindset, they were seen as a commodity and weren't really treated the way they actually should have been. There are two different trajectories. One is global payroll to domestic payroll. The other is domestic to global. Do you think this emphasis on service is the primary reason why you guys will win and the benefit of taking that trajectory that you've had?

We're pretty good at product. If you look at, for example, Shuo and myself, we're both engineers, my cofounder and I. I don't have a chief product officer. I'm the chief product officer of the business. So we're pretty good at building great products. Great products take time. And if you look at our EOR product or our contractor product, when you guys started using it versus where it is today—now it's on autopilot, and things are great, and they're working, and you rarely would have any issues. Four years ago, maybe that would have been a different story. So the only way to build an amazing product, get it in the hands of people, and learn really quickly while not destroying your reputation is to have amazing service and be super close to your customers. When people see you building—and maybe now we're less forgiven for mistakes because people see us as this big company. So maybe that mindset could and should change. But at least at the time, what I've always seen is people look at us, and when they think about the service we give, they're like, "Hey, you know what? You guys are growing super fast. You're doing amazing things. If I had run into this with any other person or any other company, it would have taken weeks to fix. But because of the way you operate, it's moving super fast." So even if there are small quirks here and there at the beginning of a new product, for example, it's worth investing in the relationship with us. And that has—I mean, it shows in the numbers. Almost 60% of our revenue comes from cross-sell and upsell into companies because they expand with us. They hire more people, but more importantly, because they actually go and buy new products. S T R I C T LY C O N F I D E N T I A L

Deel's headcount is more than 7,000 employees. Rippling's at 3,600, Ramp maybe 1,500. Can you talk about Deel as a more headcount-heavy business, and how outside observers should think about employee counts when it comes to these types of businesses?

I can't speak for those companies specifically, but the way I would look at it is, one, a lot of companies outsource customer support and a lot of different parts of their business. So it's not in their headcount, but it's hidden into their operating expenses. In our case, we don't outsource anything. We own everything from payroll to customer support to lawyers in every country, etc. So I would challenge a lot of the companies—when you're looking at their headcount, ask them how many contractors they have on support, and let's see what that headcount really starts looking like. And you'd be very surprised. But beyond this, what's been really great for us is setting up initial infrastructure. When I have a mini CFO in Brazil, a lawyer in Brazil, my first payroll and my first HR person in Brazil, I can really scale that country for a while, and I don't need more headcount. But I do need the initial ones, even in countries where these things are still pretty small—Albania, Kosovo, etc. But that initial infrastructure is very important. Over time, if you're looking at me and you're telling me, "Okay, Alex, what's going to be your headcount growth next year?" Most of it is going to be go-to-market and engineering. When it comes to the rest of the infrastructure, I'm already there. I would expect that over time as AI becomes really, really good and some of our tools become really great, then maybe we won't need—as we, let's say, double revenue, we'll be able to stay at the same headcount when it comes to customer support or some of those different things. But look, at the same time, the way we can look at it is that we are widely more profitable than most businesses when it comes to that. So if we can bring some humans to make the experience of our customers better, even if that means having a slightly higher headcount than maybe what you would expect, then I'm game for this. What kinds of companies are layering on Deel HR, Deel IT, and Deel Services? Are you seeing U.S.-based companies using these to manage their global workforce while using their domestic HR/IT providers for their domestic workforce? Is there a thesis for why companies would do all of their HR through Deel?

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At the SMB level, definitely, we're seeing a lot of customers consolidating inside of Deel. So just managing everything inside of one platform, and that's really great. You can still see customers having two different setups at the same time because, "This has been in the market for X amount of time. Let me wait a little bit to actually go and try out the U.S. product." But we're starting to make our name for ourselves here. We're seeing more and more companies that are consolidating, which is really great. Now we do have a lot of work to do there. So, hopefully, this is going to be better and better over time. Now one thing that's interesting that maybe we didn't mention on this specific topic—because I actually think we're one of the only, if not the only company, that can do this apart from maybe ADP or SAP or the others—we're actually winning big enterprise businesses. Thinking about companies like FedEx, Databricks, Verizon. It's very hard for companies at the SMB level to be able to win these types of businesses. And enterprise is actually our fastestgrowing segment. And this is where this whole bundled-unbundled mechanism really works. You're not going to sell—I'm not even going to try to sell to an enterprise today a full-stack HR solution because it's going to take me years to get there. They don't change their system of record that easily. And I don't actually need to. There's some great products out there, like Workday, etc. But on the payroll side, it's so fragmented, such a poor experience. On the EOR side, same thing, that we can really get into accounts that are at the enterprise level much quicker. And that is one of our superpowers— being able to already win amazing enterprise logos and grow with them is something that we're very excited about. We talked about a timeline where Deel goes public in 2026 or 2027. What needs to be true about the business between now and then to have a generational IPO event? And what are you looking at to say, "Okay, we're ready to have a massive IPO?" Is it unit economics, product expansion, this vision of everything on Deel coming to fruition—how do you think about it?

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My take on an IPO is that it's a great milestone for businesses, but it's just a milestone. If you were to ask me, "Alex, why would you even go public?" My key answers would be: One, we're growing super fast at the enterprise level, and being able to open our books to customers is a great value add, and being a public company can help even further. So given the growth we have there and the type of logos we're able to land, this is definitely a positive. The second part is when I think about Deel, I actually think that there's a huge opportunity to build a true global brand that people love at the HR and payroll level. If you think about HR and payroll, there are so many key moments and key events in the life of a person. You get your salary. You get your payslip. You get your mortgage letter. It's such an intimate relationship that you have with your end users, yet no one has actually ever cared enough to build something that really resonates with employees or contractors. So I think we have an opportunity to build a really great brand. And if we can build a really great brand, enabling people to own a piece of the company so we can all grow together is something that we'd be very excited about. To your specific question—well, from a pure unit economics, profitability, EBITDA, growth, revenue perspective—we're already larger than a lot of the different companies that are out there from the public market. So the way I think about this is we'll go when the time is right. The company is only six years old, so I don't have any investor pressure. I don't have any employee pressure. People are very much here to help us build the business, and we're very focused on that—all of the infrastructure, SOX compliance, our leadership bench, our executive bench. I don't know if you've seen, but we've added a chief risk officer, a chief compliance officer, a new general counsel in the first part of H1. There are still a few leadership hires we need to make happen. And yeah, when we're all ready, we'll look for the best timing to go. This transcript is for information purposes only and does not constitute advice of any type or trade recommendation and should not form the basis of any investment decision. Sacra accepts no liability for the transcript or for any errors, omissions or inaccuracies in respect of it. The views of the experts expressed in the transcript are

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those of the experts and they are not endorsed by, nor do they represent the opinion of Sacra. Sacra reserves all copyright, intellectual property rights in the transcript. Any modification,

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copying, displaying, distributing, transmitting, publishing, licensing, creating derivative works from, or selling any transcript is strictly prohibited.

Read the Original sacra.com/research/alex-bouaziz-deel-bundle-unbundle-strategy Sacra, 5 November 2025. Reproduced in TOP Venture format for LP reference.

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Wed 14 Oct

San Francisco

Sneha Revanur Founder & President, Encode AI

ARTICLE 4

T H E W I L L I A M S R EC O R D · 1 0 M AY 2 0 2 3 · Q U I N N CAS E Y

Sneha Revanur ’26, founder of Encode Justice, advocates for youth voice in AI regulation

Photo courtesy of Sneha Revanur

While many students spend their lunch break chatting with friends in Lee Snack Bar, Sneha Revanur ’26 often holds Zoom meetings and takes phone calls to advocate for artificial intelligence regulation. Revanur is the founder of Encode Justice, a youth-led organization that fights for human rights and justice in the age of AI for which she currently serves as president. The organization — composed of 600 students from 40 countries — recently sent an open letter to Congress and the White House Office of Science and Technology demanding that leaders include young people in their efforts to ensure that AI is fair and ethical. Inspired by an article about the racial bias in software used by the criminal justice system, Revanur began her tech advocacy at 15 years old — when she volunteered to help S T R I C T LY C O N F I D E N T I A L

defeat California’s Proposition 25. Revanur, who is from San Jose, Calif., noticed the lack of a substantial youth voice in the campaign against the proposition, which would have replaced cash bail with a similar algorithmic system. She rallied her peers and partnered with the American Civil Liberties Union of Southern California and others to successfully stop the measure. “At that point, it was a pretty energizing victory for us,” Revanur said in an interview with the Record. The victory inspired Revanur and her peers to found Encode Justice. “We realized that we already had this amazing team assembled [and] we already had youth who are thinking

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about these issues,” she said. “So we decided to keep our mission alive and become an organization.” “AI is such a powerful technology [whose] implications are still entirely unknown, and it’s getting more and more advanced,” Revanur explained. Encode Justice originally focused on the use of AI algorithms in bias, privacy, and surveillance. In the nearly three years since its founding, the organization has expanded its scope to include AI’s effects on social media and labor displacement. “I think we have expanded to look at all those issues — making sure that AI uplifts human society and can be an ally and not an oppressor.” Revanur helped draft the Youth Open Letter on AI Risks, in which Encode Justice joined nine other youth organizations to advocate for the inclusion of young voices in AI regulation and to demand concrete regulatory measures. The letter also acknowledges the “growing tension,” as Revanur describes it, between present-day and future, longer-term AI risks. After the publication of the letter, Politico described Revanur as “the Greta Thunberg of AI” for her efforts to call on policymakers to change regulations. She admits, however, that the rigor of a liberal arts education has posed some challenges, especially given her busy travel schedule during her first semester at the College. “When it comes to a small liberal arts college [where] you have five people in your class, being absent consistently is not the best thing,” she said. Fortunately, Revanur found that professors expressed understanding and support for her advocacy work. Such support, she said, inspired her

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decision to attend the College in the first place. “I think one of the reasons why I chose Williams was because, at a school like this — a community like this, there is so much support for the work that you’re doing,” she said. Revanur, a prospective political economy major, hopes to attend law school and continue work in tech policy after graduation. While she maintains excitement for leading Encode Justice, she described the importance of passing it down to a younger leader soon. “I think it’s really important that it stays in the hands of a true young person and not just myself for the rest of my life,” she said. “Even once that does happen, I do hope to stay involved in this work and to work on tech policy and make that my career — albeit in a different way.” Revanur stressed the importance of youth participation in regulating AI and policy-making. “The age distribution of Congress skews towards people who are very old, very out of touch with technology, and who did not grow up in a generation in which they were surrounded by machines at their fingertips,” she said. She pointed to older lawmakers’ technical illiteracy about AI and social media, like what she described as odd questioning of Mark Zuckerberg during congressional hearings. “I think it’s really important that we have younger voices pressing on leadership to actually take action on issues that are genuinely of concern to us,” Revanur said. “If not, we’re going to continue having leadership completely drop the ball on these issues.”

Read the Original williamsrecord.com/464206/features/sneha-revanur-26-founder-of-encode-justice-a dvocates-for-youth-voice-in-ai-regulation The Williams Record, 10 May 2023. Reproduced in TOP Venture format for LP reference.

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PODCAST 5

80,000 HOURS · 8 JUL 2026

Sneha Revanur on how a small team of activists helped pass America’s landmark AI safety laws 80,000 Hours Podcast, episode #246, with host Zershaaneh Qureshi. Episode summary

The episode in a nutshell

Six years ago, aged just 15, Sneha Revanur founded the AI advocacy nonprofit Encode — back when AI felt like a niche issue. Now the world’s caught up with her, and she’s ready to share everything she’s learned about the politics of AI.

Sneha Revanur founded the AI advocacy nonprofit Encode at the age of 15. Six years, two landmark state laws, and an OpenAI subpoena later, she argues that political advocacy is among the most neglected ways to make AI go well.

Encode has grown from a grassroots youth organisation to spearheading an unlikely coalition of AI-exposed groups — family-first conservatives, grieving mothers, Hollywood actors, and AI safety researchers — with the strength to take on $125m-funded anti-regulation lobbyists.

She outlines her pragmatic approach to influencing AI policy from the outside, and makes the case that state-level bills don’t need to be individually transformative to matter. Each win raises the bar for the next, building the political power and leverage needed to help regulation keep pace with capabilities. And the fact that an unlikely coalition of grieving mothers, family-first conservatives, Hollywood actors, and AI safety researchers can overcome anti-regulation lobbyists with $125 million in funding suggests that Big Tech’s playbook is backfiring.

So far, Encode’s strategy of taking many experimental swings has netted major victories (including California’s frontier AI safety bill, SB-53, and New York’s RAISE Act) as well as some disappointing setbacks. Going up against Big Tech hasn’t been easy. In 2025, OpenAI subpoenaed Encode’s general counsel at his home, with a sheriff’s deputy arriving while he was having dinner with his wife. The fallout went viral, resulting in more attention than Encode had ever experienced — and Sneha was forced to decide how hard to push back against a company she’d need to negotiate with for years to come.

Topics covered

– How the AI industry’s crypto-inspired anti-regulation strategy is not “AGI-pilled” – Why AI advocacy doesn’t have to be held back by the slow pace of policy – How mutual trust can hold together the unlikeliest of political allies – Advice for aspiring AI advocates — including how to balance political persuasion with rigorous reasoning

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If you do everything, you will win. Sneha Revanur

Listen to the Episode 80000hours.org/podcast/episodes/sneha-revanur-ai-advocacy 80,000 Hours Podcast #246, 8 July 2026. Episode summary from the publisher; listen to the full conversation at the link.

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Wed 14 Oct

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Dan Griggs Chief Financial Officer, Fin

ARTICLE 6

FIN IDEAS · 2 MAR 2026 · EOGHAN MCCABE

There is exactly one way that SaaS can be saved Intercom just passed $400M ARR with violently re-accelerating growth

Image: Fin Ideas

The predicament that the SaaS industry is in is not that surprising. No, we didn’t quite realize that AI was going to S T R I C T LY C O N F I D E N T I A L

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commodify code. But we did know that in the face of disruption, a force not new to tech in any way, the only way to have a place in the future is to destroy your past. The failure of essentially all software companies to do so in the age of agents has left them in an extra sticky spot now that the stock market is less excited about conventional software.

In this post, I’m going to offer Intercom, the company I run, as a case study to help me explain how SaaS companies can be saved, and share the things we did, starting three years ago, to find relevance in this new world. We’ve found ourselves being referred to as the poster-child for success as a late stage SaaS company in AI, and I’d like to first share some numbers and background context to help you understand why that is.

Recent coverage of our pivot and new trajectory by NYT

Three years ago, our future was looking pretty bleak. I jumped back into the CEO role after a two year hiatus while sick, when we were heading quickly towards negative growth. All SaaS growth rates fell as the ZIRP days waned, and ours fell extra hard due to an unfocused business strategy that led to poor product market fit. A month later, ChatGPT was announced and we all began our collective, gradual, and still ongoing journey to try to understand what it all means. I’ll give you the simplified meme version of the story first—“step 1: AI; step 2: ????; step 3: profit”—because I’ll be explaining the how shortly thereafter. But, in summary, we launched our new service agent, Fin, in the summer of 2023, and our business began to violently recover thereafter.

overall growth rate each year for the past two years, and are now on our way to being the fastest growing, large software company (per our knowledge), private or public, in the world. This is structural acceleration that comes from the aggregate of two businesses, one being the hypergrowth business Fin growing at ~3.5X and about to be half of our revenue early next year.

We’re now at $400M ARR overall, with Fin about to pass $100M. But most remarkably, while growth rates amongst our peers have continued their decline, we’ve doubled our S T R I C T LY C O N F I D E N T I A L

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Our agent driven re-acceleration in the opposite direction of the rest of the industry

For anyone in this industry, particularly if you’ve been in it for a decade or more, you’ll know that the chart above has essentially never been seen before. It’s so strange, it’s been hard for us all to believe. For everyone else, please take my word for it that what just happened at Intercom is kind of insane. Anyway, I want to talk about destroying the past, but before that, some acknowledgements. We had a lot in our favor that got us out ahead of the journey that everyone else must now take. For one, we were desperate for new growth. We were performing far worse than average, we had less to lose. That makes hard decisions less scary. Beyond that, we had a CEO change. It’s far easier for someone new to come in and say they don’t like how the last guy did things and rip everything up. CEOs who’ve been in seat the whole time have to wrestle with their egos and blind spots to see that great change to their own plans is the only way. And finally, we were in the right place at the right time. Conventional service software was so obviously going to be decimated by agents, and we had been building AI bots with our own AI team for years. We didn’t have a standing start. But we made plenty of strong and brave decisions as well, the essence of which I’m asking you to do now too: We turned our back on everything we held dear. We actively, S T R I C T LY C O N F I D E N T I A L

literally killed our old business. We followed the only path out of this mess, which is actual creative destruction. In a world of agent abundance, the workflow tools sold by our industry are clearly far less important, and also must drastically change. Agents don’t need workflow tools, and the humans working with the agents need different tools too. The tough pill you must swallow is that if you can’t become an agent company, your CRUD app business has a diminishing future. But what about cannibalization? “I’ll damage the revenue from my workflow tools if I pump my customer base with agents which don’t need those tools.” YES, YOU WILL. And if you don’t, someone else will gladly oblige. This is why we call it creative destruction. At Intercom, we destroyed so many things, big and small. We ripped up our old values, and created new, disruptive ones which we then hired and fired against to drive the behavior we needed in this new world. We rewrote our mission to focus on our agent goals. We changed our targets to Fin revenue. We switched up our board, removing “mature and experienced” leaders for startup founders. We moved our R&D focus to be nearly 80% on Fin, while that business was still a single digit percent of our revenue. We created a whole new brand, and a separate site, with a separate $1M .ai domain— ouch—and drove 100% of our paid traffic to it.

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Every bit of marketing effort said Fin Fin Fin, not Intercom. And was risky, big picture brand and positioning marketing to hopefully pay off later vs incremental performance marketing to definitely pay off that quarter. Again, while Fin was a single digit percent of our revenue. All because we needed the market to give us a new look for a new category. We aggressively promoted and compensated our AI team above others. We grew it from ~6 to ~60 people in 3 years with real, Phd level AI scientists and researchers. We built out our own AI, and trained our own foundational models. (More on that soon.) This slow work behind-the-scenes hurts when your nearly 30k customers are asking for new features. Almost all product launches were about Fin. All podcast interviews, all events. We announced that we would spend $100M of our cash reserves—of course, a paltry figure now —back when many were convinced AI was pure hype. We actively managed our entire customer base to a new, risky pricing model—we invented “outcome based pricing” that everyone in the agent space now talks about—that focused monetization on our helpdesk and agent combo, while reducing pricing for everything else, killing ~$60M ARR in the process.

SOURCE

We did not hold back on the creative destruction. And that really is the only idea I’m trying to sell here. We deserted our past to make way for our future. To my peers in software: This shit is insanely hard. (And if it’s not hard it’s unlikely you’re doing it right.) The shift from onprem to cloud wrecked many companies, but the change was not nearly as fast. And while it proved quite difficult for the previous generation to adapt quickly enough to keep up with my own, the shift in approach, skillset, go-to-market, and more was not nearly as dramatic. But, still, this shift is possible. Little, old, left-for-dead 15 year old Intercom did it. You can do it too! You have the brand, the customer base, the cashflows, and the access to debt. And you have the workflow tools that can be adapted for their new future for use alongside your agents too. Most of you have started moving towards this world already, but in contrast to what most AI-pilled technologists believe, I don’t think it’s too late if you haven’t! The tech is moving so fast, but customer adoption in many places will remain slow. Many large software companies will die and be bought for parts, but many will survive. As someone who’s been grinding alongside you for decades in this industry, I know how scary this time is. I want you to survive it and win. All it will take is destroying everything you love. Good luck.

Read the Original ideas.fin.ai/p/there-is-exactly-one-way-that-saas Fin Ideas, 2 March 2026. Reproduced in TOP Venture format for LP reference.

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ARTICLE 7

FIN IDEAS · 26 MAR 2026 · EOGHAN MCCABE

The age of vertical models is here

Image: Fin Ideas

Last week we quietly shipped the most significant new technology in the customer service agent category since we started it three years ago. It’s a brand new model for Fin trained by our AI Group called Apex, and it’s objectively the highest performing, fastest, and cheapest model for customer service. It beats the very best models in the industry including GPT-5.4 and Opus 4.5.

language, chat and email) customer conversations are now running on Apex. Since day 1, the Fin engine has comprised a system of models, and last year we started replacing the offthe-shelf models with our own, custom trained on our proprietary data. But the core answering model was always a frontier labs offering—initially versions of GPT and recently Sonnet 4.0. But now that core answering model is Apex 1.0.

In this post, I’ll share the news of this launch, the implications it will have for our category, but most importantly, I think, the implications this has for the frontier labs landscape.

This model resolves customer issues at a materially higher rate than any other model available. One of our largest customers in the gaming space saw their resolution rate improve overnight from 68% to 75% (i.e. a reduction in unresolved conversations of 22%). We’ve never seen a jump this large from a single improvement since we started Fin.

The news

Fin was already the highest performing and most sophisticated agent in the customer service space, consistently beating our impressive competitors like Decagon, Sierra and more at an average win rate in the 70s. It operates at tremendous scale, now resolving almost 2M customer issues per week, a number that’s growing at an exponential clip. In its short life it’s grown to nearly $100M in recurring revenue. As of last week, ~100% of all (English S T R I C T LY C O N F I D E N T I A L

But importantly it’s also dramatically faster, has fewer hallucinations, and is far cheaper than all other available models—all factors that weigh significantly in the consideration of companies deploying these agents to their service operations. This is an extraordinarily difficult thing to achieve. And we owe this breakthrough to the foundational research coming out of our 60-person AI group run by Fergal Reid. But even for elite teams like his, this cannot be 42

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replicated without the domain specific proprietary evals that comprise our billions of human and agent customer service interaction data points created by our Fin resolution engine, which had already been hand tuned to be the most effective in the category. Training with this system makes our setup a flywheel whereby we can continue to train new models that improve at the edge of our system’s abilities. Put another way, I expect that the results we’re enjoying with Apex 1.0 are just the tip of the iceberg.

there’s lots of different niches of nature… And I think we should be able to see more speciation. And you don’t need this oracle that knows everything. You kind of speciate it. And then you put it on a specific task. And we should be seeing some of that because you should be able to have much smaller models that still have the cognitive core.

What this means for the customer service agent category

The frontier labs still have the very best models, but the open-weight models are not that far behind. So it’s not hard to see pre-training as a commodity of sorts. Where we think the frontier will move next is to post-training. And Karpathy’s prediction is exactly what we’re seeing with Apex (and Cursor’s Composer 2) and what we’re going to see significantly going forward.

Service is arguably one of only two or three categories where generative AI has thus far had a material commercial, economic, real world impact. The other being coding, and perhaps the other being the legal industry. The TAM in each of these spaces is insanely large ($250B-$1T?) and as a result they are hotly contested by multiple companies, which have been aggressively capitalized. We believe that the winners in such spaces must and will become full stack AI companies. And we’ve already seen this just last week with Cursor making the first such move, with Fin being the second. As features become ~free to build, the technology factors that will differentiate the players will be the AI under the hood, and if you’re using the same general purpose off-the-shelf model as everyone else, you have no durable differentiation. This means that our competitors will indeed need to eventually release their own models. But we see them just starting now to hire for the talent required to do this and so we think we likely have at least a year head start on the space. Interestingly, 2-3 years ago, this is not how I imagined AI applications would play out. I thought that the points of differentiation would be all of the things we built around the third party models. The AI game will humble you and no doubt make at least some of my predictions in this post eventually look dumb too. What this means for the AI industry at large

In a podcast interview last week, Andrej Karpathy said: I do think we should expect more speciation in the intelligences. The animal kingdom is extremely [diverse] in the brains that exist And

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As such, the labs are in an interesting position where on one hand the horizontal, general purpose models are actually over-serving the market for specific use cases. E.g. their models are more generally intelligent than is needed for customer service. And on the other hand, the open-weight models are more than good enough where high quality domain specific post-training can make the resulting models superior at the special purpose jobs, and in the ways that matter to that particular job. E.g. in service, the soft factors really matter, like judgement, pleasantness, attentiveness (as well as the hard factors mentioned prior, like the ability to effectively resolve problems, quickly and cheaply). Personally, I’m still very bullish on the labs. And we remain very heavy customers of Anthropic, whether as part of the broader system of models used for the Fin Engine, or with the depth of our usage of Claude Code in our engineering org. Yet classic disruption (a la the late, great Clay Christensen) is now at their door. The only way out is to disrupt themselves by building cheaper specialized models too. And the only way to do that is to acquire the evals (or the companies with the evals) needed for that specific task. Which means there will be some interesting data partnerships, or M&A consolidation, or you’re going to see some hyper specific model providers who go it alone and compete with the labs head to head. Likely all of the above. In the meantime, we’re happy to be the only vendor in our space with a custom model that’s also objectively superior to everything else out there. And we’re excited to deploy it far and wide for the benefit of end customers everywhere. Our 43

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next announcement that’s coming very soon will help us do exactly that.

SOURCE

Read the Original ideas.fin.ai/p/fin-apex-1-0-model-announcement Fin Ideas, 26 March 2026. Reproduced in TOP Venture format for LP reference.

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Tue 13 Oct

Mountain View

Neil Hoyne Chief Measurement Strategist, Google

PODCAST 8

S I D E C A R S Y N C · E P. 2 6 · 1 9 A P R 2 0 2 4

Unlocking Customer Lifetime Value and Embracing AI with Google’s Neil Hoyne Sidecar Sync, episode 26, with hosts Amith Nagarajan and Mallory Mejias. 52 minutes. Episode summary

In this episode, Amith & Mallory sit down with Neil Hoyne, the Chief Measurement Strategist at Google. As Google's top measurement strategist, Neil has led over 2,500 engagements with the world's largest advertisers, helping them acquire millions of customers, improve conversion rates by over 400%, and generate billions in incremental revenue. His first book, "Converted: The Data-Driven Way to Win Customers' Hearts," was published in 2022 by Penguin Random House. In this discussion, Neil shares key insights from his book, including the importance of focusing on customer lifetime value (CLV) rather than short-term metrics. He explains how

SOURCE

organizations can apply the concept of member or donor lifetime value to better understand and nurture their most valuable constituents. Chapters

– 0:00 Customer Lifetime Value and AI – 7:56 Understanding Customer Lifetime Value and Application – 13:02 Customer Lifetime Value Analysis in Marketing – 20:00 Customer Lifetime Value and Potential – 28:14 Metrics and AI Impact on Business – 39:33 Organizational Change in the AI Age – 42:48 The Impact of Generative AI

Listen to the Episode sidecar.ai/blog/unlocking-customer-lifetime-value-and-embracing-ai-with-googles-n eil-hoyne Sidecar Sync podcast, episode 26, 19 April 2024. Episode summary from the publisher; listen to the full conversation at the link.

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Tue 13 Oct

Mountain View

Gopi Kallayil Chief Business Strategist, AI, Google

ARTICLE 9

I BY I M D · 7 A P R 2 0 2 5 · G O P I K A L L AY I L

Communities, companies, and consumers: How AI can do good Used boldly and responsibly, AI could drive powerful positive change, argues Google’s AI business strategist.

Image: I by IMD

Artificial Intelligence is perhaps the most far-reaching technology ever created. It could prove more significant than the advent of the printing press in 1440, electricity in 1762, and the automobile in 1886. AI has existed as a concept for decades, but now it’s coming of age. All of us can engage with it using everyday language, and the architecture and computer power exist to make it come alive. Its capabilities are still being built, and we’ve yet to see what humans will do with it. However, AI is so pervasive and rapidly growing that

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it will develop exponentially, profoundly altering nearly every field of human existence and changing how we live and work in ways we can’t imagine. While we’re excited about the potential of AI, we understand that with advanced technologies come challenges, such as potential bias in algorithms, privacy violations, malicious use, job displacement, social manipulation, and the creation of uncontrollable AI systems. This means responsible

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development with robust oversight and ethical considerations is crucial. In 2018, Google published seven Principles of Responsible AI (see list at the end of the article) and appointed a governance team responsible for monitoring and reporting on compliance. We want everyone working at Google and those who interact with us to understand that these are the core AI principles we follow and to be consistent with them, ensuring that AI is bold and responsible. Amplifying natural intelligence

Let me demystify artificial intelligence. To do that, we must first look at a unique human capability: natural intelligence (NI). This involves learning from the past, responding to new situations, comprehending intricate ideas, creative thinking, emotional insight, and flexibility. It is the type of intelligence that created the ballpoint pen. It’s a simple instrument with elements – from the development of the forging process to communicating thoughts on tablets with rudimentary ink to the invention of the compression spring and plastic – that have taken thousands of years to develop. Yet, for all the insights, breakthroughs, and capabilities our natural intelligence has brought us, it is a limited resource. For example, if your leadership team consists of five people, then that team possesses the intelligence of five people. But what if, with this same team of five, you could tap into the intelligence of 50 people? This is what AI is about and what computer scientists have been trying to do: mimic our natural intelligence in computer systems and amplify that capability, emphasizing the word amplify rather than replace. AI systems not only amplify the capabilities of the human brain, but they also mimic different types of cognitive functions. Systems that mimic the right side of the brain (more intuitive and creative) are what we broadly refer to as generative AI, while systems that mimic the left side (more quantitative and analytical) are called analytical AI. Each system serves a different function, and each can complement the other. How analytical and generative AI differ

Analytical AI explores existing data to understand patterns, make predictions, and gain insights. These systems perform complex calculations, analyze large datasets rapidly, and allow for systematic workflow problem-solving and optimization. By prioritizing objective analysis, analytical

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AI can identify patterns and trends, providing valuable insights that might otherwise be difficult for human analysts to detect. Generative AI systems create new data. They use deep learning neural network models to generate new content that mimics human creation – images, text, music, programming code, and even entire pieces of artwork. A neural network is an AI method that teaches computers to process data in a way inspired by the human brain. These systems recognize patterns and understand and respond to human emotions. They adapt to unpredictable situations and generate innovative solutions to complex problems. Just as the human brain integrates both hemispheres to function effectively, advanced AI systems are being developed to combine generative and analytical capabilities, allowing these integrated systems to manage a broader range of tasks with greater sophistication. For example, generative AI can enhance predictive analytics (a subset of analytic AI) by enriching data models and generating possible scenarios, improving the accuracy of forecasts. Google’s AI strategy targets three audiences

Google declared itself an AI-first company in 2016. Our AI Strategy is underpinned by the belief that AI can inspire and empower people in many fields, including healthcare, security, energy, transportation, manufacturing, and entertainment. We’re helping three audiences – consumers, communities, and companies – to reach their highest potential with AI. Let me explain this strategy one audience at a time. Audience 1: Consumers

Consumers (i.e., the eight billion-plus humans on the planet) use various Google products to manage their lives. Seven Google products – Search, Gmail, Android, Chrome, Google Play, YouTube, and Maps – are each used by more than two billion people monthly. We’re asking: “How can we enhance the experience for consumers by using the power of AI across all of these products?” Take one example: search. Historically, if you were searching, you had to navigate to a rectangular box on Google and type in words to find the information you were looking for, and you needed to be fairly precise. You had to

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“What is it?” We can’t even describe it. The launch of Google’s Circle to Search feature on your smartphone means you can use intuitive gestures like circling, scribbling, highlighting, and tapping to learn about what’s on your screen without switching apps. Audience 2: Communities

Access to education and healthcare, as well as climate change, are among many pressing societal problems. We’ve been asking at Google: “Can we use AI to solve any of these issues?” For example, floods affect more people than any other environmental hazard. Flood-related disasters have more than doubled since 2000, with nearly 1.5 billion people exposed to significant risk annually. Upgrading early warning systems to make accurate and timely information accessible could save thousands of lives. Engineers at Google asked: “Can we use AI to predict flooding and provide those who live in the area earlier notice?” Our team explored the potential of machine learning to create better flood forecasting models. They collaborated with academic researchers to combine the best hydrological physics-based flood simulations with our AI approach. They built a flood prediction model where AI runs simulations to determine the millions of ways in which the river could behave, depending on the level of water, how fast rains flow, which embankment collapses, which tributary is swelling, and which dam has to release water because it’s at capacity. The AI-powered model runs simulations and can predict flooding, indicating the different combinations by which the river can behave. This would be difficult to do using traditional methods. The team tested this system around the Ganges in India. Nearly half a billion people live nearby. During the monsoon season, the river will likely flood, affecting agricultural land, homes, and livestock. The people living in the area get one day’s evacuation notice, so the flooding causes a great deal of property damage. The tests were a success, and now, during the Monsoon season, the system captures all this data and starts predicting: “The Ganges river will flood the town of Patna in the next five days,” and so on. That information is distributed to the local authorities and the general population through Google alerts and Google Maps, giving people time to evacuate. Google forecasting is now available in more S T R I C T LY C O N F I D E N T I A L

than 100 countries. AI-powered, AI-generated, and AIdistributed – this is an example of AI benefiting the worldwide community. Audience 3: Companies

Google enables organizations to use AI to work smarter, make better decisions, leverage powerful tools to streamline operations, gain deeper insights, bring innovative ideas to life faster, and build sustainable and successful businesses that continue to thrive and grow in an increasingly prosperous world. This is best illustrated in the case study of Omoda, an innovative Dutch fashion retailer. The company had been undergoing extreme change due to the acceleration of online shopping, the variety of available payment methods, and the introduction of fast fashion, resulting in a return rate of up to 50% of the items sold. Omoda asked us: “Can we build an AIbased system to predict whether an order will be returned? And if so, how much of the order?” So, we built a model looking at historical data where we knew the items with a higher probability of being returned and new real-time data, which included variables like payment methods or order size. When an order came in, the system would combine historical and real-time data to get a prediction. Omoda used the prediction to change its operating process model. The AI model successfully predicted returns for 7075% of orders, reducing returns by 5% and increasing profit margins by 14%. The company plans to optimize the model further to reduce CO2 emissions and enhance personal sizing recommendations. How can AI enable your business strategy?

As you launch your business strategy, ask yourself the following: What is your plan for growth this year? What are the priorities and challenges? Then, most importantly: How can I use AI to enable the strategy? To determine the AI capabilities that can enable the strategy, you’ll need: 1 An understanding of where AI is now and where it’s

going. Be ahead of the curve, and then constantly look inside and outside your industry to learn how others are using AI.

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2 A spirit of experimentation. It’s hard to predict what’s

next because new developments and capabilities are always emerging. You want to get in early and continually try tiny experiments to see what succeeds.

3 Smart people who have AI skills and talent. If you

don’t have those people internally, you can partner with external organizations that have AI capabilities. And this could be technology companies like Google and Microsoft or consulting firms like Accenture.

Whether it’s faster and more efficient access to information, flood forecasting, or finding financial and eco-friendly solutions for excessive product returns, the steps are the same: identify a problem, determine the desired outcome, and then ask how AI can provide a better solution.

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Google’s Principles of Responsible AI 1 Be socially beneficial. 2 Avoid creating or reinforcing unfair bias. 3 Be built and tested for safety. 4 Be accountable to people. 5 Incorporate privacy design principles. 6 Uphold high standards of scientific excellence. 7 Be made available for uses that accord with these

principles.

Just as the human brain integrates both hemispheres to function effectively, advanced AI systems are being developed to combine generative and analytical capabilities. Gopi Kallayil, Chief Business Strategist for AI, Google

SOURCE

Read the Original www.imd.org/ibyimd/audio-articles/communities-companiesand-consumers-how-ai -can-do-good I by IMD, 7 April 2025. Reproduced in TOP Venture format for LP reference.

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Tue 13 Oct

San Francisco

Kate Norton VP, Business Strategy & Finance, Netflix

ARTICLE 10

HBS WORKING KNOWLEDGE · 6 AUG 2025 · JAMES BARNETT & STACY STRAABERG

Freedom, Fear, and Feedback: Should Other Companies Follow Netflix’s Lead? Culture can spur or depress innovation, says Hubert Joly, whose case study examines how Netflix built a unique workplace culture—and what happened when it was tested.

Image: Ariana Cohen-Halberstam with assets from AdobeStock

Companies looking to create a culture that celebrates creativity might take a page from the ultimate Silicon Valley playbook: Netflix’s 2009 “culture deck” championing freedom with responsibility. To woo the best and brightest, the streaming giant rejected top-down decision-making and annual performance reviews, offered unlimited vacation and loose expense policies, and demanded high-performance standards with frequent, frank feedback. Meta's Sheryl Sandberg called the deck one of the most important documents ever to come out of the Valley. S T R I C T LY C O N F I D E N T I A L

“Culture can be seen as fuzzy and difficult to define,” explains Hubert Joly, a Senior Lecturer at Harvard Business School and former CEO of Best Buy, who co-authored the case study “Netflix’s Culture: Binge or Cringe?” “If your culture is defined by vague values like customer centricity or integrity, it’s hard to execute. Netflix created a culture around a singular, powerful idea—freedom with responsibility—that set clear expectations designed to support top-performing employees and the belief that great talent improves results exponentially.” 50

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But when the streaming company’s growth slowed, Netflix faced questions about whether its culture was in part to blame. “There are many examples of Netflix succeeding through its culture, but what do they do when things stop working?” asks Joly, who worked on the case with HBS Baker Foundation Professor Leonard Schlesinger. “Netflix must test whether the original idea of the culture is still valid or whether they need to tweak it, given the fact that the context has changed.” The tale offers lessons on how to create, adapt, and sustain that squishiest of fundamentals—culture—at a time when instability in both the markets and the political environment tests companies, employees, and customers. Netflix’s unorthodox example also shines a light on how the management basics of a company—from vacation policies to performance reviews—help or hurt innovation. Wanted: Achievement and autonomy

To many, Netflix is as synonymous with streaming entertainment as Kleenex is to tissues. Founded in 1998, Netflix grew from a mail-order DVD sale and rental service with 300,000 subscribers in 2000 to a streaming service and original content producer with over 300 million global subscribers and $39 billion in revenue in 2024. Many observers credit Netflix’s success to its unique workplace culture, which is based on the strong point of view developed by co-founder and former CEO Reed Hastings, that highly-talented people don’t like policies, they want freedom. Hastings elaborated in his book No Rules Rules: Netflix and the Culture of Reinvention: “If you give employees more freedom instead of developing processes to prevent them from exercising their own judgment, they will make better decisions and it’s easier to hold them accountable.” He added: “If your people choose to abuse the freedom you give them, you need to fire them and fire them loudly.” Four key ingredients

The 124-page culture deck emphasized: 1 Talent density. Netflix favored smaller teams of highly

talented individuals, especially in creative and technical roles, and terminated average performing staff, using the refrain: “adequate performance gets you a generous severance.” Employees were let go if they could not pass “the Keeper Test”—that is, whether a manager would try

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to change an employee’s mind if the employee quit. The idea: Fill each role with a star. 2 Regular, honest feedback. Early on, Netflix did away

with performance reviews, finding them too ritualistic and bureaucratically burdensome. Instead, the company expected staff to give routine, candid feedback to other employees, regardless of rank. Withholding disagreement or constructive input was on par with being disloyal to Netflix. Employees were also encouraged to highlight their own mistakes, known as “sunshining.”

3 Non-hierarchical decision-making. To speed decisions

and encourage creativity, Netflix used an “informed captain” model for decision-making. A staff member owned a key decision, aiming to achieve Netflix’s goals rather than “please their boss.” Managers remain involved to share context and advice, not to dictate or control the outcome.

4 No formal vacation or travel and expense policies.

Employees had unlimited vacation, which Hastings explained helped to simplify procedures and reduce costs. “Most important, the freedom signals to employees that we trust them to do the right thing, which in turn encourages them to behave responsibly,” Hastings wrote in No Rules Rules. Expenses and travel were managed by a five-word guideline: “Act in Netflix’s best interest.”

The downsides of “no rules rules”

Netflix’s culture could be polarizing. For example, some employees appreciated being surrounded by a dream team of uber-talented employees, while others were paranoid about being terminated and existed in a state of fear. “Sunshining” could cause an employee to lose their job if it revealed significant mistakes. International employees had varying levels of comfort with Netflix’s practices. For instance, Japanese culture is traditionally non-confrontational, making the frank and frequent feedback challenging, the case says. But in the Netherlands, the more direct, the better. And in some European countries, local labor laws conflicted with Netflix’s approach. Netflix allowed for some adaptations to its culture depending on the country. Tough times, and doubling down

Netflix soared higher during the COVID-19 pandemic, driven 51

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by grateful customers locked inside and hungry for entertainment. But despite Netflix’s meteoric rise, the company hit a rough patch in May 2022. Competition in the streaming space had intensified and Netflix faced slowing revenue, a decrease in its share price, and its first loss of customers in a decade. The challenging period left some observers wondering if the same culture that propelled Netflix to its highest heights now held it back. Joly asks: “In Netflix’s case, what do you change? Do you revisit Netflix’s purpose to “entertain the world”? Or do you go for the strategy: is it time for another reinvention like when Netflix shifted its value proposition to original content? Or do you tweak the culture?” Netflix did rebound mightily. By the third quarter of 2023, Netflix began to turn the corner, outperforming Wall Street predictions by adding 8.8 million subscribers that quarter, the largest quarterly increase since the early days of COVID19. Revenue also increased 8 percent year-over-year that quarter. After the share price had dropped down from a high of close to $700 in the fall of 2021 down to below $200 in the spring of 2022, it reached close to $1,200 in the summer of 2025. How did they do it? Primarily by tweaking their strategy and value proposition, e.g., introducing an ad-based subscription model, cracking down on password sharing, getting into videogames, live sports, launching a Broadway and opening experiential “Netflix Houses”. In contrast, they chose not to change their chosen culture, making only minor tweaks to the language. “From a culture standpoint, they didn’t change it; they reinvigorated it,” says Joly, “vindicating a culture that lets top performers, well, perform.”

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Epilogue: Levers for managers

Joly suggests three tools for companies to help shape their culture and the need to correct course on culture: Business levers

These include changes leaders make that directly impact the business, like shifting strategy or tweaking operations, that also directly speak to culture. In the case of Netflix, Joly says the culture had gotten complacent; shifting strategy to go after big new markets like live sports and gaming allowed the company to lean into its original culture again. Management levers

Joly points to important signals companies send about their cultural priorities based on who they include and who they exclude, and who they reward and why. Companies need to align the nuts-and-bolts of human resources with the culture’s goals. “Who you put in positions of power, who you invite to meetings, incentives—all these things impact culture,” Joly says. He says that things like what managers emphasize in their business meetings—e.g., starting with people, moving to the business, and leaving financials for last—reinforces a culture that prioritizes talent and customers. Leadership behaviors

Cultures are sometimes described as hard to change. Joly does not believe it is true and adds: “The way you change behaviors (culture) is by changing behavior. Companies must ask: “Are your leaders culture carriers?” Joly says. “Do they model the behaviors you are trying to espouse?” Joly also believes in the role of intrinsic drivers of human behaviors such as autonomy, meaning, human connections, psychological safety, learning and a growth mindset, in enabling extraordinary levels of performance.

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He believes that leaders can and should shape their behaviors in ways that make these ingredients come to life so that they can “unleash human magic”.

“

James Barnett and Stacy Straaberg are case writers at HBS and coauthors of the case “Netflix’s Culture: Binge or Cringe.” Joly, Hubert, Leonard A. Schlesinger, James Barnett, and Stacy Straaberg. “Netflix’s Culture: Binge or Cringe?” Harvard Business School Case 522-096, June 2022. (Revised March 2024.)

Netflix must test whether the original idea of the culture is still valid or whether they need to tweak it, given the fact that the context has changed. Hubert Joly, Senior Lecturer, Harvard Business School

SOURCE

Read the Original library.hbs.edu/working-knowledge/freedom-fear-and-feedback-should-other-comp anies-follow-netflixs-lead Harvard Business School Working Knowledge, 6 August 2025. Reproduced in TOP Venture format for LP reference.

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ARTICLE 11

FORTUNE · 29 SEP 2026 · SAGE LAZZARO

How Netflix is using AI to personalize streaming Generative AI is the driving force behind a sharply rising number of platform functions, user interactions, and creative processes at Netflix today.

Illustration: Simon Landrein

Before AI was “AI,” Netflix was already a fervent early adopter, pushing the boundaries of algorithms, big data, and machine learning for two decades. In the post-ChatGPT era, the streaming company is finding creative new ways to boost its operations with the technology. Generative AI is the driving force behind a sharply rising number of platform functions, user interactions, and creative processes at Netflix today. The company earned high marks in the Fortune 2026 AIQ 75, ranking 17th overall on the list, which looks at how Fortune 500 companies are using AI dayto-day in their businesses. This embrace of AI is fitting for a company famous for being at the forefront of innovation, with Netflix having pioneered the streaming video format now common across the entertainment industry. Netflix’s goal is to be a great partner to filmmakers and serve viewers what they want to see, says Ritwik Kumar, Netflix’s vice president of AI strategy and innovation, who’s led machine learning at the company for almost a decade. As he S T R I C T LY C O N F I D E N T I A L

sees it, maintaining those principles through this period of rapid technological change is both Netflix’s mission for this moment and its greatest challenge. “Stumbling on that would be pretty bad for our business,” he notes. “So I would say not being at the cutting edge of giving our creators the tools that they want or personalizing things for our members are the biggest risks for our business.” Many of Netflix’s current AI transformation efforts draw upon its roots in personalization. “In this generative AI era, we have quite a strong conviction and growing body of evidence that we could do way better for our members when it comes to getting them the right piece of content they would fall in love with at the right moment,” says Kumar. A new “conversational interfaces” concept, currently in pilot

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testing, seeks to move beyond the cumbersome and restrictive routine of typing into the search box. Instead, users can talk and have a deeper conversation with the Netflix platform about what they want to watch. Kumar believes voice is the next frontier for the platform, allowing for a greater exchange of information to indicate the viewer’s mood. “What we saw when we ran a pilot … is that you can have a much more fluent dialogue with the system,” he says. “Actually, people have a lot more to say about what they are in the mood for. Or even if they aren’t sure, they would explore in ways that were previously just impossible.” Other Netflix executives have presented the feature as a way to cut through the overwhelming number of options the streamer offers. AI is helping Netflix fine-tune what its audience sees in other ways, too. The company’s new AI-enabled ad format allows advertisers to connect the “vibe” of the ad to whatever the viewer is currently watching. For example, when a user pauses Stranger Things, the ad that appears on-screen can now directly reference elements from the show, eliminating what Kumar describes as a jarring transition from content viewers are deeply engaged with to something completely irrelevant. Using AI to get shots that would otherwise be impossible or prohibitive is similarly Netflix’s pitch for the technology in the creative process. The company doesn’t dictate that content producers use AI or any specific tools, Kumar says, but it does go out of its way to make AI available to creators. And in the event that Netflix’s selection of mostly third-party tools turns out to be inadequate for a filmmaker’s vision, members of Kumar’s teams work directly with the filmmaker to build a more bespoke solution for their needs.

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The streamer has leaned heavily into AI for content production, noting in July that roughly 300 titles on the platform this year have used generative AI at some stage in the production life cycle. In March, Netflix paid $587 million to acquire Ben Affleck’s AI film-tech startup, InterPositive, which is developing “AI-powered tools built by and for filmmakers,” according to the company. Netflix is also currently building an AI animation studio called INKubator for short-form content. That said, artificial intelligence is a sensitive issue in the industry Netflix operates in. Regardless of what otherwise impossible shots the technology may have brought to life, the use of AI in creative works remains contentious for many. AI was a central issue in the 2023 contract negotiations between Hollywood studios and the Screen Actors Guild– American Federation of Television and Radio Artists, and when director Danny Boyle said he used generative AI in the making of Netflix’s upcoming Oscar hopeful Ink, it was headline industry news.

The Hollywood Reporter called Netflix’s use of AI to re-create the voice of the late Gene Wilder for a new Willy Wonkainspired reality-TV show “a rather unsettling choice, and might strike some as a bit tasteless, if not outright creepy.” On the risk that content made with AI, no matter how good, might affect viewer interest or brand trust, Kumar believes that it won’t matter if it’s done right. While a component here or there may be enhanced with AI, he says, there is still a lot of art and traditional creative decision-making at play. He doesn’t believe Netflix has anything wholly generated by AI on its platform and thinks the notion that a filmmaker could use AI to simply prompt their way to a compelling shot “feels fantastical.”

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“We take our lead from our members telling us what they’re loving or not,” he says. “So the idea is to not dwell too much on technology. It’s just a tool.”

“

This story appears in Takeaways from the Fortune AIQ 75, a five-part series examining what Fortune’s 2026 ranking reveals about how companies are putting AI to work—from agentic workflows and industry-specific applications to the operating models behind largescale adoption.

Not being at the cutting edge [is one of] the biggest risks for our business. Ritwik Kumar, VP of AI Strategy and Innovation, Netflix

SOURCE

Read the Original fortune.com/2026/09/29/how-netflix-is-using-ai-to-personalize-streaming Fortune, 29 September 2026. Reproduced in TOP Venture format for LP reference.

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AREA

Tue 13 Oct

San Francisco

Elias Rimer AI Model Behavior Engineer Lead, Notion

ARTICLE 12

NOTION BLOG · 30 SEP 2024 · ELIAS RIMER

How I learned to stop worrying and love AI The new Notion AI pulls from your collective knowledge to create game-changing updates and summaries.

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Image: Notion

Stop worrying. Start using Notion AI.

That “Send me an update on your work” quicksand feeling? Yes, we know it well. But the new Notion AI can help you find answers fast from across your team’s knowledge base. Free yourself from endless searching and frantic scrambles to gather SOURCE

information. No more awkward “Sorry to bother” moments. Welcome to the future of work, where AI does the drudgery, your cortisol levels plummet, and you find time for that mythical creature called a “lunch break.”

Read the Original notion.com/blog/how-i-learned-to-stop-worrying-and-love-ai Notion Blog, 30 September 2024. Reproduced in TOP Venture format for LP reference.

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PODCAST 13

S E Q U O I A C A P I T A L · L O N G S T R A N G E T R I P · E P. 1 5

Notion’s Ivan Zhao: The Refounder Sequoia Capital’s Long Strange Trip, episode 15, with host Brian Halligan.

Image: Sequoia Capital

Episode summary

Ivan Zhao, founder and CEO of Notion, joins me to introduce a new contender in the founder mode debate: jazz mode. Ivan has a different take than Jack Dorsey's circular org chart or Brian Armstrong's player- coach approach. He thinks hierarchy is human nature, and that you can't flatten it away SOURCE

but you can build a company that improvises like a jazz band instead of marching in formation. Ivan is the king of refoundings. He's done it twice, once from a small apartment in Kyoto with five employees left, once from Cancun the day he got early access to GPT-4. His advice for any CEO who's calcified and wondering if it's time to blow it up: feel the AGI first, then trust your body when it tells you to move.

Listen to the Episode sequoiacap.com/podcast/notions-ivan-zhao-the-refounder Sequoia Capital, Long Strange Trip, episode 15. Episode summary from the publisher; listen to the full conversation at the link.

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AREA

Wed 14 Oct

Stanford

Rob Livingston Chief Financial Officer, Nu Holdings (Nubank)

ARTICLE 14

COLOSSUS · OCT 2026 · GABI MARQUES

Coming to America After facing down regulators, oligopolies, and corruption in Latin America, Nubank founder David Vélez faces his biggest challenge yet: the United States

Photos: Gabriel Ortiz

David Vélez materializes on the eighth floor of Nubank’s headquarters in São Paulo at 9:53am, and greets me in Portuguese with a thick Spanish accent. “I’ll be with you in seven minutes,” he says. I set up in a conference room. At S T R I C T LY C O N F I D E N T I A L

10am, he takes his seat across from me and asks, in Portuguese, which language we’re doing this in; we settle on English. He is sporting a gift from his wife: a purple bracelet on his right wrist. 60

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I grew up only four miles from here, and first remember hearing about Nubank in 2015 from a friend who boasted about her new credit card. She told me she’d been sent a link, signed up, and, a few days later, a purple card appeared at her house. To a teenage girl in Brazil hearing about it from older friends and cousins, the plastic, purple, no-fee card sounded cool. To my dad, it sounded like a scam. He worked at Itaú, one of Brazil’s largest banks and Nubank’s biggest competitors. I was reminded that we already had perfectly good credit cards, and that I already had an account at Itaú. There was even money in it.

In New York, when I first used the app, I remember feeling oddly proud of my new bank account, similar to the feeling you get when one of your compatriots wins gold at the Olympics: You may have had nothing to do with their achievement, and you may have known nothing about the person before that moment, but suddenly you feel they represent the very best parts of you, or the things you aspire to. Brazil has produced its share of successful companies, but few have become global reference points, the kind people on other continents know and point to as world-class. Nubank is on the precipice of becoming one.

In 2018, I moved to the U.S. Every time I came back to Brazil I’d notice more purple cards being pulled from pockets when a check arrived for dinner. It sounds quaint, but purple was a shocking color for a credit card or any consumer product in Brazil. It sparked questions, which its owners were eager to answer: There really were no fees, the customer service was unusually good, you could do all your banking from your phone, etc. They’d drone on, until at last, they’d exhale, “You should get one!”

Whether it does depends largely on the success or failure of Vélez’s current challenge: taking Nubank to the United States, its first market outside Latin America. His task is no longer to prove that a Brazilian startup can beat the Goliaths at home or in its neighborhood, but that it can compete and win on a global stage.

I didn’t. But before my move back to Brazil in 2025, I needed a new bank account, a business account, and a credit card. I asked friends where I should go. Nubank, obviously. From an apartment in New York City, I downloaded the Nu app. By then, Nubank had become the largest digital bank in Latin America and one of Brazil’s largest financial institutions. Today, it serves over 140 million customers across Brazil, Mexico, and Colombia, including 118 million in Brazil alone, where more than 60% of the adult population uses the app. In the second quarter of 2026, Nubank crossed $1 billion in quarterly net income, and nearly $6 billion in revenue. It has been publicly traded on the New York Stock Exchange since December 2021, and is now worth more than $60 billion. Part of what makes Nubank’s rise so compelling is how improbable it once seemed. From its first pitch deck, one analogy has been used again and again to tell Nubank’s story: David versus Goliath. Vélez, Nubank’s Colombian founder and CEO, has gone head-to-head with Brazil’s largest, most profitable, and most entrenched companies. He angered them by lowering fees and rates, by bringing more than 31 million previously unbanked people into the financial system and giving more than 18 million their first credit card, and by forcing legacy institutions to adapt to the consumer expectations that Nubank abruptly reset.

In the course of reporting this story between São Paulo and Miami, I spoke with Doug Leone, the longtime partner at Sequoia Capital who backed Nubank in its earliest days. “There are the Elon Musks and Steve Jobses of the world, and they’re fantastic,” he told me. “But there are also these people who are still early enough in their careers that we don’t fully see what they might become. Bill Gates wasn’t Bill Gates for the first 20 years.” “I think David is one of those guys,” Leone said. “He has vision. He executes. He’s tough as nails. He’s lovable. He’s nobody’s fool. And look, I haven’t sold a single share of the company stock. That doesn’t tell you everything. But it tells you something.” Vélez was born in Medellín, Colombia in 1981. His parents were both entrepreneurs, as were all 15 of his aunts and uncles. “There was a lot of entrepreneurial DNA being served for breakfast, lunch, and dinner,” he told me. By age five, he was working at his father’s button factory. On weekends, the Vélez family would drive to their finca, a small house in the Colombian countryside. He remembers riding horses, swimming in the pool, and spending time with his two younger sisters. Yet outside the finca, Medellín was at war. The Colombian government was fighting the major drug cartels, and bombs exploded often in the streets. It was not uncommon for people you knew to be kidnapped in broad daylight.

“I remember needing to sleep on the floor,” Vélez said, S T R I C T LY C O N F I D E N T I A L

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“because Pablo Escobar said they were going to bomb the city, and I was worried about the windows of my bedroom shattering. One day I wore a bunch of sweaters because I thought that if I wore enough of them, the bullets wouldn’t hit me.” He was six years old. When he was eight, the Vélez family moved to Costa Rica. His parents wanted their kids to sleep in their own beds and wander outside without fear of being shot. They left behind their home, friends, family, the kids’ school, Saturday lunches with grandparents, and weekends at the finca. “I wouldn’t necessarily use ‘traumatic’ as a word,” he told me. “But it was life-changing, obviously.” “My parents were able to create an environment where I felt safe. That gave me a sense of confidence that no matter what happens, no matter what the environment is like, we’re going to figure it out. We’ll be fine. We’ll know how to move forward, persevere, and succeed.” “But I never really felt that I was fully local,” he said. “I never felt that I fit in. I always described myself as a Colombian, and there was always a sense of being an outsider. It’s a feeling that’s followed me and continues to be a part of my identity.” His father opened a button factory in Costa Rica, rebuilding the same business in a new country. Vélez spent summers there doing odd jobs, making leather patches for jeans, helping wherever he could, looking for ways to earn a little money. At 12, he talked his dad into selling him a cow. It seemed like the greatest investment ever. The cow had a calf, making teenage Vélez the proud owner of two cows. By the time he was 18, he had a herd of six. He sold them and took the money to Stanford University, which had become an improbable dream he managed to pull off. Nobody from his school in Costa Rica had ever gone to Stanford, and few Stanford students could trace their pocket change to a sale of six cows. The day the acceptance email hit his inbox remains one of the happiest in his life. “He was a foreign-born kid who found his way to Stanford,” Leone said, when asked about the first time they met. “By the time you do that, you self-select.” Vélez graduated from Stanford in 2005 with a degree in management science and engineering and the bug to start a business, but no particularly good idea for what it should be. Instead he interned at Goldman Sachs for a summer, then joined Morgan Stanley for two years before moving into private equity at General Atlantic (GA). S T R I C T LY C O N F I D E N T I A L

His first deal at GA was an investment in Brazil’s commodities and futures exchange, BM&F. It was one of the largest investments the firm had ever made. Vélez, who was 26 and the closest thing GA had to a Brazilian, was asked if he’d like to open their first office in São Paulo, where he spent the next two years. Between the summers of 2008 and 2010, he spent more and more of his time and energy on financial services. By the fall of 2010, he decided to return to Stanford for business school, which he envisioned as a vacation during which he’d figure out what business to start. Then a classmate, David George, learned through Doug Leone that Sequoia was looking at Latin America, and introduced him to Vélez. A couple weeks into his first quarter of business school, Vélez drove the two miles from Stanford to Sequoia’s Sand Hill Road office to meet with Leone. In the two minutes it took to walk from Leone’s office to his car in the parking lot after the meeting ended, Vélez received an email from Michael Moritz, Sequoia’s other major partner, telling him to come back inside. He wanted to meet Vélez, too. “When we ran Sequoia, we were two different cats, but we saw a lot of business things the same way,” Leone said. “With David, we quickly saw him exactly the same way.” “When we interview people at Sequoia, there’s an expression we sometimes use: someone is a half-pager. A half-pager is someone you meet, ask all the questions you want to ask, and 35 minutes later you only have half a page of notes. Then, once or twice a year, you meet someone and the whole hour flies by, and you have two or three pages of notes because they’re so interesting you don’t want to forget anything. David was one of those.” At the time, the concept of BRIC (Brazil, Russia, India, and China) was still new. Sequoia had already expanded into India and China, and Brazil seemed like it might be next. Leone and Moritz needed someone to help them figure out whether it should be, and to potentially lead their efforts in Latin America as a whole. Vélez got an offer to join part-time while at Stanford Graduate School of Business (GSB), with a mandate to help answer that question. “Part-time” turned out to be a loose description of the arrangement. “He worked full-time in business school,” Leone said, “and he worked full-time at Sequoia.” Vélez would get to his desk at Sequoia by 5am. He’d talk to founders and source deals until 8–9am, then leave for 62

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classes at Stanford. When his classes were done, he’d return to Sequoia around 4–5pm and stay a few more hours before going home to do homework. On Wednesdays, the business school had no classes. On Tuesday evenings, Vélez would accompany Leone on a private jet to Brazil; they’d land in São Paulo Wednesday morning and spend the day in meetings before returning in time for Vélez’s Thursday classes. During one such trip, in the span of 34 hours, Leone and Vélez had three meetings to sign term sheets for three different deals: an online travel agency, an agriculture technology company in Londrina, and a capital markets company (XP Investimentos). The last one still stings. They had a term sheet to invest in XP at a roughly $200 million valuation, and passed. “Horrible decision,” Vélez said, clearly still not over it. “XP is worth something like $10 billion now. It would have been a 50x investment.” Leone’s memories of those trips are somewhat more esoteric. He remembers eating bacalhau (a salted cod dish most foreigners find disgusting), getting pitched on a petroleum investment by Eike Batista (whose $35 billion net worth soon became negative-$1 billion after he was prosecuted for bribing public officials and placed under house arrest), and of course the terrible traffic. About a year and a half into the experiment, Leone started leaning negative on Brazil. He thought too many tech companies started their pitch the same way: “We are the so-and-so of Brazil,” as Leone described it. “Pick your favorite U.S. company. The Uber of Brazil. The DoorDash of Brazil. Every time you back those kinds of businesses, you may have an exit, but they’re not fundamental businesses. There’s no innovation.” After some 40 company meetings and zero deals closed, Sequoia ditched its foray into Brazil. Leone called Vélez to give him the news. It came as a shock. Vélez had spent nearly two years trying to make the Brazil office work, in part because he believed that Sequoia could lead a meaningful reinvention of the entire Latin American tech ecosystem. Still, the decision wasn’t entirely surprising. Plus, there was a consolation prize: Sequoia offered Vélez a job in California on generous terms. By that point, they’d watched him work non-stop for two years, and they liked his nose for companies. The offer was to work with growth equity investments internationally.

To the despair of Vélez’s mother, he turned it down. Instead, after he graduated from GSB, he showed up back at his family’s house in Costa Rica, unemployed. Two months later, he was back at Sequoia; this time, he was standing in front of Leone and Moritz with a few slides. “That’s what I’d wanted for a very long time,” Vélez told me. “I remember being at General Atlantic, even before [Sequoia], hearing the entrepreneurs and thinking, I want to be in that seat. They’re having all the fun. They’re making the hard calls, the tough decisions. As an investor, I just get to write checks and say, ‘Go do it.’ It felt too easy.” He was pitching for a seed check to build a financial services company, starting with credit cards, in Brazil. Just a couple months earlier, Leone had told Vélez that Sequoia didn’t want to do anything in Brazil, period. “I’ll tell you the truth,” Leone said of the check they did write. “Half of the investment was almost part of his package when he left [Sequoia]. I won’t call it severance, but you get the idea. We felt some guilt to do right by this young man. But I also argued—and other people who knew him felt the same way—the young man has game. He’s an outlier. Maybe he can do something.” Sequoia gave him $1 million to start the company in exchange for 10% equity, but the investment came with one condition and one disclaimer. The condition was that Vélez had to find another $1 million from a local fund. The disclaimer was that this wasn’t a bet on Brazil or on financial services; it was a bet on him. Vélez got the other million from Kaszek Ventures; by July 2013, he’d raised the $2 million seed round. Sequoia wouldn’t make another early stage investment in Brazil for more than a decade. When Vélez first moved to Brazil, he endured what he still calls “the most painful experience of my life.” He’d tried to open a bank account.

As he stepped through the bulletproof doors of a São Paulo bank, the metal detectors went off. Two armed guards approached him. They soon realized he was not there to rob the bank; he had simply forgotten to take his phone out of his pocket. Still, they asked him to leave. Back outside the building, he put everything he owned in a locker, then came back through the doors. Once inside, he waited 40 minutes to see a branch manager. He made two more visits over the next five months (plus

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multiple phone calls to the call center, including one while he was physically at the bank branch) before he was given a bank account that cost him $20 a month and came with a monthly credit card interest rate of over 16%. He says the whole experience made him feel like a criminal, or like a pauper begging for the right to become a customer. Which is what led to his simple idea. Look at the most valuable companies in Brazil, he thought: they’re banks. Financial services was one of the biggest and most profitable markets in the world and growing fast. In Brazil, it was an oligopoly: five banks controlled roughly 90% of the market. They were all located on the same street—Faria Lima, São Paulo’s Wall Street—hired the same people, and never changed. The cost of their complacency was borne by the customer through high fees, obscene interest rates, and terrible customer service. They succeeded almost in spite of themselves. Their options sucked, but customers were still desperate to make the best use of what options they had. Vélez’s idea was to build a new option, starting with a credit card. That was it. The idea had come together during his two months of unemployment in Costa Rica, after Sequoia’s decision to give up on Brazil. Vélez spent time at his parents’ home looking at benchmarks. Capital One had gone after a similarly concentrated credit-card market in 1990s America. Its insight was that credit cards did not have to be a commodity; you could capture and use more data, build better credit models, segment customers by their credit risk (and price accordingly), start narrowly with one product, and earn the right to expand from there. (Nigel Morris, Capital One’s cofounder, would eventually become a Nubank investor.) Another inspiration was Tinkoff Bank, now T-Bank, the first digital-only bank in the world. It was founded in Russia in 2006 by Oleg Tinkov, who also studied Capital One and began with credit cards. At the same time, smartphone adoption was skyrocketing in Brazil, where one of the highest rates of mobile app usage in the world led The Wall Street Journal to call the country “the social media capital of the universe.” When he describes the experience of connecting the dots, an almost mystical look comes over Vélez’s face. He was brought back to earth by Roelof Botha, a partner at Sequoia, who walked Vélez through everything he was unqualified to do: He was neither a Brazilian nor a native Portuguese speaker. He’d never worked at a Brazilian bank or at a credit card issuer. He’d never underwritten credit, dealt S T R I C T LY C O N F I D E N T I A L

with Brazilian regulators, or built a technology company. He wasn’t even a computer scientist. Vélez assumed Botha was building toward the conclusion that, therefore, he shouldn’t pursue his idea. Instead, Botha’s conclusion was: you have to hire people who are all the things you aren’t. Edward Wible came first. The American was not a conventional CTO candidate; he was a computer science undergraduate who wound up on the partner track in private equity, then moved to Buenos Aires after graduating from INSEAD to start a transportation startup because, as he told me, “Every time I met an entrepreneur, I wanted to be them instead of me.” His first attempt failed almost instantly. He piloted it with Scanntech, a retail-tech company Sequoia had invested in, but disagreed frequently with management, tried to change everything, and got fired. Vélez, who sat on Scanntech’s board, had been watching from the investor’s seat. Now, Vélez got back in touch with him. “He said, ‘I liked that you were trying to change everything, and I liked how you went about it. I liked the energy, I liked the violence. I need someone who’s willing to put his hands on something, and I know you’re available,’” Wible recalled. “‘So why don’t you move to Brazil with me, and let’s start a bank?’” “I think I thought about it for only a few hours,” he said. What attracted him wasn’t banking per se. He had what he describes as an almost desperate desire to prove he could pivot his career and build something beautiful: to solve a problem elegantly by making something objectively and undeniably better, faster, and cheaper. Next was Cristina Junqueira, one of the roughly 100 people on Vélez’s co-founder speed-dating list. If he was the outsider who had identified the problem, and Wible the technical builder who wanted to solve it, Junqueira was the Brazilian industry veteran with knowledge and experience of Goliath. She’d spent five years at Itaú Unibanco, including running a major piece of its credit-card business. Frustrated by the pace of change at an incumbent bank, she quit and vowed never to work in financial services again. But she hadn’t left to start her own business. She just wanted to work on something that mattered to her, she said. Her speed-date with Vélez went two and a half hours. That night, she couldn’t sleep. “I put my head on the pillow, and I remember turning to my husband and saying, ‘This is what I have to do. This is it.’” One of Junqueira’s former bosses told Vélez that if she were 64

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a state of matter, she would be gas: she expanded to fill every empty space in a room. Even today, when you ask her what she does at Nubank, her answer is: “whatever needs doing.” Officially, Junqueira is chief growth officer and U.S. CEO; unofficially, she is also Nubank’s most visible spokesperson.

understood. But he has no regrets. “I think it’s the engine that powers our efficiency ratio,” he said. “[The company] is really innovative down to the core, in ways sometimes you can only see by touching the product. There are no vendors at the core. It’s very efficient, and we have the ability to always make it more efficient.”

“There was a bit of a rebellious angle to them,” Vélez said of his co-founders. “Cris rebelling against the banking establishment, Ed against the conventional way of building a technology company.” Each had developed an aversion to the way things were being done in Brazil, which manifested itself in nearly everything they touched.

Clojure, the programming language he chose, was by banking standards similarly unorthodox. It was less radical than it sounded: Clojure runs on top of Java, which banks already used, allowing Nubank’s system to draw on the mature ecosystem of Java tools and libraries. What appealed to Wible was that Clojure imposed more guardrails on how software was written. Certain low-level technical choices were pre-decided, which meant the team could spend more time focused on the consumer problems the company wanted to solve.

Starting with the office. Brazilian banking was embodied in glass towers on Faria Lima. Vélez, Wible, and Junqueira’s first office, by contrast, was a small rented house in a residential neighborhood called, of all things, Brooklin. It was two floors and had a dog. The team called it the Casinha, the little house. What sold them on it was the name of the street: Rua Califórnia. The Casinha became an effective recruiting filter. Some people looked at the dingy little house and laughed trying to imagine it as a national bank, while others saw the discrepancy between the current reality and the ultimate goal as mad but inspiring. For Wible—who had arrived in Brazil with a backpack, slept on Vélez’s couch for a few days, and spent the earliest weeks working out of coffee shops—the Casinha had a luxurious amount of space and privacy. He lived on the second floor and worked downstairs for eight months. “We needed the space,” he said, when asked what finally made him move out. “It was like, ‘Ed, get out!’” The next day, his floor was packed with desks. Then there was purple. “It looked like something that arrived from outer space,” Junqueira said of the very first card. Today the company’s purple is so recognizable in Latin America that it’s hard to appreciate how strange it was at the time. “You have to give David credit for that,” she said. “He had a lot of conviction about the purple, and he was completely right.” The card started conversations simply by existing. Increasingly, the same was true of the core technology. Most banks bought their core banking tech from the same handful of legacy vendors and stitched the pieces together, making their services virtually indistinguishable. Nubank swore off vendors and decided to build its own core. This was, according to Wible, much harder to do than he initially S T R I C T LY C O N F I D E N T I A L

“There are a lot of technical reasons, too, but most of the really important reasons for me are business related,” Wible said. “It’s about focus and consistency. Maybe some people don’t like it, but everybody moves faster when you don’t have to constantly relitigate those decisions.” Between the Casinha, the purple, and the decision to build the technology from scratch, Nubank was already putting out the signal of an anti-bank: If you come work here, you don’t do it the way you did it at your last job; you do it our way. The sentiment was reinforced by the company’s name: Nu. In Portuguese, nu means naked. Like in English, it can be used to convey simplicity, transparency, or having nothing to hide. It also worked as an ambigram: turn the card upside down, and nu still reads as rightside up. And when spoken, of course, nu is identical to the English new, which is what the startup was. (Today, the company primarily goes by “Nubank” in Brazil, and “Nu” internationally. For the sake of simplicity, it will be referred to henceforth by its historical and still most recognizable name, Nubank.) On April 1, 2014, just over a year after the company was founded, Nubank’s first transaction went through—on the third try—at a bakery in Brooklin, where the team ordered pão na chapa (bread grilled with butter) and beer. It was R$33. The receipt is framed on a wall at headquarters today. Over the following year, the business developed two simple revenue streams: At every swipe, Nubank earned a slice of the interchange fee generated by the transaction; if a customer carried or financed a balance, Nubank also earned interest. Interchange was the main source of revenue, and by 65

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operating entirely digitally—with no branch network and a much lighter cost base—it could live on those two streams while eliminating fees and charging lower interest rates than incumbent banks. Their bet was that by making the product cheaper and the experience better, customers would market Nubank themselves. It worked. In May 2015, Leone pitched a follow-on investment in a Sequoia growth meeting; the vote was unanimous in favor. By June 2015, the purple card had a waitlist of 100,000 people. By December 2017, Nubank had three million customers, nearly all of them by word of mouth, without a dollar spent on customer acquisition. (To this day, the company has no sales team, and 85% of its customers have been acquired organically.) “It wasn’t just a few people. It was this phenomenon of people trying to invite other people, completely unincentivized,” Wible recalled of the phenomenon I’d observed from afar in New York: People recommending the purple card to their friends, not for points or referral bonuses, but because they just wanted them to have it. “I remember thinking, ‘What’s going on here?’” he said. “None of the stories I knew about building banks had a virality component.” On Thursday, December 15, 2016, Vélez was traveling in the U.S. when he woke up to the news that the Central Bank of Brazil had decided to shorten the settlement period for credit-card purchases (i.e., how quickly merchants must get paid) from roughly 30 days to two. The proposal, part of an economic stimulus package from President Michel Temer and finance minister Henrique Meirelles, was rough news for every card issuer. If someone bought a TV with a credit card, the bank had almost a month before it had to pay the store for the TV. The Central Bank’s new rule would compress that window, overnight, to 48 hours.

Nubank suddenly needed a lot more working capital which, only a bit over two years since its founding, it simply didn’t have. Vélez flew back to São Paulo that day. The founding team met to figure out what to do. Vélez remembers Nubank’s CFO, Gabriel Haddad Silva, running the numbers and concluding that they would need $600 million in additional working capital, essentially overnight. It wasn’t just a financing problem. Nubank had one product: a credit card. There was no savings account, no debit product, no deposit base underneath it. It was still a startup living off the S T R I C T LY C O N F I D E N T I A L

capital it raised, nowhere near breakeven. If approved, the Central Bank’s new rule could put the company out of business, or force it into a fire sale. That Friday was Nubank’s end-of-year party. They’d had tshirts made to celebrate, but no one felt festive now. Vélez remembers standing in front of the company, which by then had 350 employees, all of whom knew there was a sword hanging over them. “We were very anxious, thinking, is the company even going to be here on Monday? I decided to be very open with everyone… I told them, ‘I don’t have the answers. We don’t know how we’re going to survive this. But we’re going to fight like hell and figure out how to stop it.’” They decided to fight publicly, and not to sugarcoat their position: The Central Bank was out to kill competition. Just as new entrants were finally chipping away at a hated oligopoly, the state was seeking to crush them with impossible capital requirements. Over that weekend, the story spread. Newspapers began covering what the change could mean for Nubank and other small entrants. By Sunday, December 18, the story was everywhere: the purple card was being forced out of business. By Monday morning, hundreds of thousands of Nubank customers made its cause viral on social media, flooding the Central Bank’s Facebook page with pro-Nubank hashtags. By around 11am, Vélez received a message from Ilan Goldfajn, president of the Central Bank, summoning him for a talk. Vélez and Junqueira both went. Vélez remembers walking into the room tense and concerned, expecting a fight. “Relax,” Goldfajn told them as soon as they walked in. “There are no changes happening.” The proposal would linger for a while, he explained, but the two-day rule wouldn’t be imposed; Nubank’s customers had made sure of that. The next day, December 20, the Central Bank announced it wouldn’t impose the rule. The response on social media was ecstatic. Back at headquarters, the team finally donned the shirts they’d made for the end-of-year party, which were emblazoned with the words, “The future is purple.” The new 26,700-seat Inter Miami stadium at Miami Freedom Park is all white, with two exceptions. There are the giant posters of Lionel Messi, Casemiro, and other players in pink jerseys wrapping the building, and there is the purple logo over the entrance: Nu Stadium. 66

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The stadium opened in April as part of a multiyear partnership between Nubank and Inter Miami, which also includes a Nu Plaza outside, a Nu Club inside, the ‘nu’ logo on the back of the team’s jerseys and, on this particular Thursday morning, pretty much everywhere else. Every screen in the empty stadium glows purple, rotating between the words “Welcome to the Nu Era” and “Trusted by over 140M people.” Out of the 300 or so people invited to this event, about 60 of us are reporters. Ever since Nubank received conditional approval to establish a national bank in the United States on January 29, 2026, the U.S. launch had been intensely anticipated by those of us who follow the company. The approval meant that by mid2027, at the latest, Nubank would need to have a U.S. bank up and running. My invitation came a few weeks after another record quarter for the company, with net income reaching $1 billion for the first time, but the event itself was mysterious and open-ended. Surely it was to officially launch their U.S. venture, but perhaps something else was in store for us, too? We’re steered into one of the stadium’s VIP rooms, where we’re offered a choice between coffee, smoothies, and alcohol, all of which somehow seem equally appropriate here before noon. A stadium voice announces that the keynote is about to begin, and directs us to an auditorium downstairs. The music is clubbier than anyone needs at 11am, but that, too, seems appropriate. Purple lights sweep the room and the stage. The event is being streamed live, which adds a certain tension among the staff. The lights go down and a hype video begins: the three cofounders intercut with an animation of the company’s story. One million customers in two years; ten million in five; one hundred million in ten. A world map made of white dots appears; one turns purple, around São Paulo. Then another and another. The camera pulls back until the whole map is visible and, eventually, every dot turns purple. When it ends, the crowd claps as Vélez walks onstage in what appears to be the same dark purple polo sweater he was wearing in the video. I can’t tell whether this was carefully planned or an honest wardrobe mistake. Either seems plausible. He gives the founding story, then moves through what happened next: Nubank conquered Brazil, where it is now the largest private financial institution in the country by customer count. Mexico, Nubank’s second-largest market, S T R I C T LY C O N F I D E N T I A L

grew at an even faster rate, becoming the country’s largest digital bank in under seven years. The growth rate has been faster still in Colombia, where in under six years it became the fourth-largest financial institution by deposits, and leads the market in growth and credit card issuance. The central point Vélez wants to make is that the product travels because “people everywhere want to be treated well. The problems we are solving are global.” This is Junqueira’s cue. She takes the stage in a white striped dress and impossibly thin heels, hair and makeup immaculate. She is a natural performer. Junqueira moved to Miami earlier this year to run the U.S. business, recently enough to experience American banking as a foreigner herself. For someone new to the country, as I can attest, getting established can be quite burdensome. No credit history often means waiting months to get approved for a card; proving your identity or address can mean repeated trips to a branch; and different parts of the same bank (in her case, mortgage and credit) often don’t share the information they already have about you. Such challenges are faced by millions of underbanked Americans, of course, in addition to foreigners. To purple lights, loud music, and applause, Junqueira makes the expected announcement: Nu is launching in the U.S. She describes the product: a high-yield savings account, a no-fee credit card with cashback, and fast, fee-free domestic and international transfers, starting with Brazil, Mexico, and Colombia, all backed by the 24/7 customer support they like to brag about. As his coup de grâce, Vélez reappears onstage to introduce Nu Global, a feeless multi-currency account that moves money across 35-plus countries and lets customers hold and trade a selection of digital assets like Bitcoin and Ethereum. By the end of the keynote, it’s clear what the “Nu Era” means, at least to the company: that its ambitions are no longer Brazilian, Latin American, or even Western Hemispheric, but global. After the keynote, reporters wait to be called into a room where Vélez and Junqueira take questions. Most have their laptops open; some sit on the floor typing furiously, trying to publish their story before someone a foot away does. Others rehearse the one question they may or may not get to ask. Notes are exchanged between bursts of work. We’re called in. Vélez enters first and goes up to every reporter in the room with a handshake, a smile, and some version of “thank you for coming.” The questions start flying. What’s the actual strategy for the U.S.? Who is the target 67

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customer? Why will it work here? What about competition? The United States has thousands of banks and a long list of fintech challengers that have died, been sold, or are fighting over a small slice of the pie. And what about Revolut? Did you see they just got their conditional approval too? Nu Global puts you in direct competition with them now. A comment? One more word? Please?

for predicting financial behavior and assessing borrower risk, has already allowed the company to raise credit limits in Brazil without raising the risk it takes on, and its AI systems now reach nearly every part of the business, from underwriting to customer service. All of which may turn out to matter as much as anything announced onstage that morning.

Vélez’s answers are calm and firm. Whatever the question, he replies with what he wants, which is just enough to count as an answer, then redirects toward the point or statistic he wants you to write down.

“Every major industry around the world has been reinvented by technology companies except banking,” Vélez told me in a one-on-one interview. “Ninety-five percent of the world’s financial services still sit with large incumbents. It’s almost like saying 95% of the world’s video delivery is still owned by Blockbuster, or JCPenney instead of Amazon, or taxis instead of Uber. That will change. It might take another decade, it might take two decades. But the biggest providers of financial services in the world will be technology companies. And we have a shot at that.”

On competition: 95% of global financial services are still controlled by incumbents, he says. Nubank’s fintech competitors may compete with each other for the remaining 5%, but Nubank’s eyes are now on the 95%. In the U.S., he explains, that prize is enormous: American retail banking generates roughly $1.2 trillion in annual revenue; even a small slice is a huge business. True, 82% of American adults already have a credit card, and 96% have a bank account. But they are paying $75 billion in fees each year and navigating, in Nubank’s view, an inefficient system that has much room for improvement. The company’s first advantage—cost—is the same one it had 13 years ago in Brazil, he says. It costs Nubank roughly $1 a month to serve a customer; for a traditional U.S. bank, the number is closer to $20. That difference alone, Vélez argues, is structural: no branches, no vendors, core technology built from scratch, a low cost to serve, and savings returned to customers as better yields, better service, and no fees. Another advantage, he says, is credit. The company started as a credit-card business, which meant learning early how to get good at credit underwriting. Over the following 13 years, that became one of Nubank’s core capabilities. More than 28 million people across Brazil, Mexico, and Colombia have since obtained their first credit card through Nubank. Along the way, it’s developed increasingly sophisticated ways to assess credit risk, including for customers with limited traditional credit histories. One question near the end finally turns to AI. Vélez joined OpenAI’s board in July, but AI is less a new chapter for Nubank than an acceleration of one it has been building toward for years, he says. The company now sits on an enormous store of financial data from a customer base it has served for years. NuFormer, its proprietary foundation model S T R I C T LY C O N F I D E N T I A L

It made me think of something Leone told me. “Early on, when there is nothing, you have to come up with these dreams for yourself,” he said. “Imagine when they had 10 people, saying they would become the most valuable financial services company in Latin America. Well, they became that. Now, what about if they can become the most valuable financial services company in the world? That is the dream. You don’t need any more motivation if you’ve got that.” Then he turned to his computer and started typing. “I’m looking for J.P. Morgan’s market cap, just for the fun of it,” Leone said, and paused to look over his glasses at the result. “$792 billion. We’re shooting for nothing less than that.” “One of the things that makes me the most proud,” Vélez told me, “is how, in an environment like Latin America and Brazil, where there has been so much corruption and unethical behavior, we’ve been able to build one of the continent’s largest financial institutions while always acting ethically, being very straight about what we do, and always sticking to that.” He credits his mother, who he says had a very strict sense of right and wrong.

Vélez’s favorite book is Gabriel García Márquez’s One Hundred Years of Solitude. Partly it’s the writing; partly it’s that there’s so much Colombia in it. He loves the families, the way parents behave with their children, the love stories, 68

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the culture. “Colombia is my origin. Those are the roots that I left,” he said. “Maybe when the storm removes the Buendías’ house, and they lose their roots, there’s something of me losing my roots, too. It’s the way García Márquez writes and how engaging it is, but also the entire story and how much it touches my own identity as somebody who was born in Colombia.” “Do the moves get easier with time?” I asked, now that he’s planning to move back to the U.S., another world again. “I think they get… I don’t know. Logistically, yes. It’s one more move. You pack your bags and go.” He paused. “But emotionally, it gets harder. Every move is an additional disappointment: failed again at putting down roots, failed again at finding a place where I feel like I belong. And now I worry about the kids, because they’re going to go through the same process.

“

“So maybe rationally and logistically, it gets easier. Emotionally, it feels a bit like another disappointment. Another failure.” “So where is home?” I asked. “That’s the big question,” he said. “We are unrooted. There is no home, and that’s the sad part about it. Since I left Colombia and went to Costa Rica, there’s been a little bit of longing to find home, to find roots. So far, I haven’t found it. “I’ve been an outsider everywhere. An outsider in Costa Rica, an outsider in California, an outsider in New York, an outsider in Brazil. Potentially back to California. Maybe California is interesting because there are a lot of outsiders there.” He thought for a second. “Home ends up being family more than a physical place,” he said, before adding: “And Nubank.”

Most banks bought their core banking tech from the same handful of legacy vendors and stitched the pieces together, making their services virtually indistinguishable. Nubank swore off vendors and decided to build its own core. Colossus

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SOURCE

Read the Original colossus.com/article/david-velez-nubank Colossus, October 2026. Reproduced in TOP Venture format for LP reference.

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ARTICLE 15

NU NEWSROOM · 6 AUG 2026

New CFO signals disciplined ambition for Nubank’s next phase of growth Rob Livingston and David Vélez discuss how part of the playbook that brought Nu to where it is will also propel it further

Image: Nubank

São Paulo, August 6, 2026 — Nubank, the largest digital bank in Latin America, released a new episode of its Nu Videocast, featuring its new Chief Financial Officer, Rob Livingston, in his first public conversation with Founder and Global CEO David Vélez. His message is one of continuity: the same credit discipline and growth playbook that built Nu, will carry it into a next phase of expansion. Why Nu, and why Rob

Livingston joins Nu with a track record of building at scale: 18 years at Capital One, most of it in the core credit business, and 12 years at Visa across general management and finance, ending as CFO of North America, its largest business unit. Along the way, he built Capital One's Canadian operation and stood up Visa's domestic business in China from the ground up. He says he had admired Nu's growth story from his years at Visa, and joined a company that has served more than 135 million customers across Brazil, Mexico and Colombia while remaining international since its first ten employees.

“We look for people who have seen the kind of scale we are beginning to reach, but who also have an entrepreneurial bent inside organizations and have worked across multiple countries,” said David Vélez, founder and CEO of Nubank.

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“The first priority here is continuity. Nu has been a great success story for 13 years, and there's no turning of the ship that needs to happen right away. My mandate is to continue that story, but also to prepare us for the next stages of our growth,” said Rob Livingston, CFO of Nubank. A credit model built for any cycle

At Nu, credit decisions integrate revenue and risk and pass through three lines of defense, and every decision must remain profitable even if losses double, so growth is never a switch a CFO or CEO can simply flip. Rather than time the market, Nu underwrites with a deliberate “pessimist bias,” says Vélez, assuming the future will be worse than the past, an approach the model has carried through four Brazilian credit cycles in its first 12 years, including the deepest recession in living memory, intact. Artificial intelligence is sharpening that edge rather than loosening it: the company's proprietary nuFormer foundation models let Nu extend more credit at the same expected loss, or the same credit at a lower loss, and have cut model development from roughly three months to about seven days, with a human still reviewing every outcome.

“While the U.S. goes through one cycle, we see several in Brazil. Financial services companies have to be antifragile: 71

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they have to have a profitable business model in every single cycle, with high or low inflation, high or low interest rates. That's exactly what we've demonstrated over 13 years,” said Vélez. A disciplined path to expansion

On expansion beyond Latin America, the message from Livingston was discipline over ambition. The United States is the world's largest financial services market, and Nu does not need a large share for it to matter.

SOURCE

The company has committed to spend no more than 100 basis points of its efficiency ratio on U.S. entry over two years, treating the period as foundational as it builds its brand, tests product-market fit and refines its underwriting, on the multi-country technology platform it has always owned. With conditional approval from the Office of the Comptroller of the Currency to establish a national bank, expected within 18 months, Nu frames the move as a bounded bet.

Read the Original nu.com/en/newsroom/company/new-cfo-signals-disciplined-ambition-for-nubanks-n ext-phase-of-growth Nu Newsroom, 6 August 2026. Reproduced in TOP Venture format for LP reference.

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Wed 14 Oct

Stanford

Justin Ferrell Strategic Partnerships, Hasso Plattner Institute of Design, Stanford d.school

ARTICLE 16

DIALOGUE REVIEW · 16 OCT 2019 · BEN WALKER

Justin Ferrell is the essential voice for design-thinking in organizations Ben Walker meets Duke Corporate Education’s Renaissance Man

Sometimes others are the best judges of your own qualities.

“People have extended opportunities to me that I didn’t see myself,” says Justin Ferrell, a guru of design-thinking from Stanford who began his career as a sports reporter on a local newspaper. “It’s not just about your skills, it’s about responding to what others see in you.” Ferrell had a boyhood dream of working at the great campaigning newspaper the Washington Post – “I’d seen All the President’s Men”. It came true – not because of his selfperceived qualities as a reporter – but because of others’ recognition of his skills as a designer. Working on a sports desk of just three people at a newspaper in St Augustine, Florida, everybody did everything. The then 23-year-old Ferrell would write match reports about highschool American football games, then lay them out on page. He learned page design from the sports editor, but longed to be involved in other events. “There are bigger things going on, I wanted to be involved in news. And sports writing is super-competitive. Something like 80 people applied for my job at St Augustine, and I probably got it because they could pay me the least.”

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Ferrell sent his cuttings nationwide (in those days, before internet news became a thing, they really were cuttings, physically chopped from newspapers). He was rejected time after time. “I sent them all over the United States, I didn’t even get an interview,” he recalls. Then, one day, a newspaper in Greensboro, North Carolina, called him. “I said, ‘Did you like my writing?’ They said, ‘Oh no, we didn’t like your writing. But the news desk passed your clippings along to us – we are the copy desk. We’re just wondering whether you wrote the headlines on these stories, and whether you laid out these pages?’” Ferrell answered in the affirmative, got an interview as a designer – and got the job. “I became a designer because the industry told me that I had more talent there than I did as a writer,” he says. After five years, he moved on to a management-level newspaper job across the state in Raleigh. Then, after just a year, he landed a job at the Washington Post, the dream fulfilled by a circuitous route – “the opportunities offered to me by other people, rather than my intentions.”

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Ferrell was at the Post for almost eight years, and when it merged with its website (they were then separate companies), he moved into digital design. When designing the Post iPad app, he read about David Kelley’s work at the Institute of Design at Stanford (Stanford d.school). He later met with a colleague there who worked with Kelley, and was, he says, “blown away by the place”. He joined a journalism fellowship, taking ostensibly temporary leave of absence from the Post, but never looked back. His family loved California. Then, at the end of the year, somebody else saw something in Ferrell that he hadn’t seen in himself. Sarah Stein Greenberg, the design school’s executive director, wanted to start a non-sector specific fellowship programme at the d.school, and wasn’t in the mood to wait. “She said, ‘We like to launch to learn, so how about we start in a few months and you be the director?’” By that autumn, Ferrell’s life had again turned on a dime, thanks to the recognition from others. There is a satisfying equivalence between Ferrell’s career and the design-thinking he now teaches at Stanford. He tells a story about a used-car salesman. “I’ve nothing against car salesmen,” he says. “But testing is not the same as selling. Instead you are trying to put your idea into people’s hands to see how they react to it.” Like the copy desk at the Greensboro paper all those years ago, they might not react to it in the way you expect them to. “What do they like about it? What do they not like about it? What kinds of questions do they have? What kinds of new ideas do they have? It’s in that feedback that your next direction emerges. You don’t want to be so close to your idea that, one, you are not open to feedback; and, two, you are trying to convince people that you have come up with the perfect thing for them.” Ferrell works as an educator for Duke Corporate Education, applying design-thinking to organizations where employees, colleagues, are leaders’ ‘customers’. “My approach to teaching is behavioural,” he says. “How do we get out of our own way so we are able to look at a situation with fresh eyes? And how do we fight the inertia to do the same things that we have always done?” Inertia, he suggests, is a stubbornly powerful force. “From an organizational perspective, when you are doing something new you are working against the status quo,” says Ferrell. “There are a lot of antibodies that keep you from moving against the stream. There are a lot of reasons why we just want to continue down the path that we were always on – from a personal standpoint it’s more comfortable. S T R I C T LY C O N F I D E N T I A L

“It turns out that we like to do things that we are good at. To stop something where we know what the outcome is going to be, to try something where we are not sure what is going to happen, is difficult. It requires a lot of intention – and a lot of support – to be able to do that.” Companies know they are supposed to innovate, but often interpret it as a mandate for piecemeal development, rather than removing themselves from the day-to-day and asking what their processes are for. “What are the behaviours we are trying to encourage, how do we view the problem from the person’s perspective? In my teaching, I try to give people the space to step back and ask: ‘Who is this for, and how do we engage with those people and get them what they need now?’” Design-thinking is traditionally applied to products and services, ideating, then iterating and testing with the market, co-creating with a customer focus. Ferrell specializes not in product design, but in organization design. The two applications come from the same source. “It’s about helping organizations evolve,” he says. “How do we develop creativity within organizations? We teach the basics of design-thinking and then turn it internal, and say: ‘How do we do this as leaders in our organizations, where the people we are designing for are our employees?’” He encourages leaders to see their employees’ needs as verbs (e.g. communicating), not nouns (e.g. email). “The question I ask is, look at the thing you already do and ask what is that thing for? If you frame the problem around the noun, with a ready-made solution, then you are more likely to create an incremental solution.” As Henry Ford famously discovered, if people could travel faster without a horse, they would no longer require the animal. Can he give an example from his own career? “Back at the Post, I was once asked to redesign the newspaper. So after a ten-month project we ended up with an incrementally better newspaper. Our mission statement was: ‘to be for and about Washington.’ If we had said, ‘Instead of taking ten months to redesign the newspaper, let’s take ten months to connect people with the local issues they care about’ – because that was what the newspaper was really for – then we might have designed a social media platform. Facebook was brand new at that time, and we might have designed something like it. We might have reached the conclusion that local is not about geography, it’s about network. My epiphany as a journalist – an industry completely changed by technology – was not that the folks in Silicon Valley were smarter than we were, 74

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but that they were asking different questions.” This ideation must be performed in a neutral space. Ferrell warns against companies falling into what might be termed the brainstorming trap – that people pass judgement on ideas when they are first touted, killing them at birth. “If you are evaluating the ideas at the same time as you are generating them, we all know that is the quickest way to shut down the generation of ideas. If you say, ‘let me play devil’s advocate’… ‘how much is this going to cost?’… well, we intentionally separate the evaluation from the generation. Not because we think that every idea is going to be brilliant. We know that the majority are not going to be. But we don’t need a high percentage of great ideas, we just need to get a few great ideas. And the best way to get to a good idea is to get a lot of ideas.” Do organizations often ask the question ‘what is this for?’ and find they don’t have an answer? “If you can no longer articulate what it’s for, you must seriously consider whether you should be doing it at all,” says Ferrell. “One of the things I noticed at the Post, and I think the same is true of other organizations, is that you start to think ‘I don’t have time to do all these other things, I don’t have time to explore the future, because I’m too busy reacting to all the inbound stuff of the present’. But at the Post I used to say, ‘well, we are journalists, don’t we get to decide what we are going to do? We edit all the time!’ “The same is true of other organizations – all the things that you have to do on a daily basis were created by you or the people you work with. Those were the products of decisions

that people themselves made. We are not stuck in this wheel. We created this wheel! If we created this wheel, we can create another one. Or we can get off.” Ferrell instils in his tutees a mindset of empowerment – that, since organizations were created by human beings, they cannot be more powerful than the people within them. “David Kelley has this phrase that self-efficacy is the belief that you can achieve what you set out to do,” says Ferrell. “Creative self-efficacy is the belief that you can achieve what you set out to do in a way that you have never done before. I think that’s a really important place to start – looking at what you currently do and thinking, ‘you know what? I can do this differently.’ Once you believe you are creative, that you have that creative self-efficacy, you look at the world as malleable.” But even in his own sessions, Ferrell rarely finds more than half the delegates consider themselves ‘creative’, at least not before he gets to work with them. At the risk of diverting into social commentary, we debate whether opportunity is equitably distributed, either in perception or reality. Does everyone have the agency to change the wheel – or get off it? “I’m not saying that opportunity is equitable,” says Ferrell. In his personal life, Ferrell does a lot of work in social justice: he knows that for many people, access to resources is not evenly distributed. “There are places that I get to go with Duke, places in the world, where opportunity is not equal,” he says. But individuals and companies can change themselves for what’s next. “These organizations can create their own future,” says Ferrell. “I think it’s just about reminding them of that, and giving them the room and the tools to do it.” — Ben Walker is editor-at-large of Dialogue

SOURCE

Read the Original dialoguereview.com/justin-ferrell-essential-voice-design-thinking-organizations Dialogue Review, 16 October 2019. Reproduced in TOP Venture format for LP reference.

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Wed 14 Oct

Stanford

James Landay Denning Director, Stanford Institute for HumanCentered AI, Stanford HAI

ARTICLE 17

STA N FO R D R E P O R T · 4 M AY 2 0 2 6 · STA N FO R D STA F F

Stanford merges AI and data science efforts under single institute The combined institute will retain the Stanford HAI name and be helmed by computer scientist James Landay. Co-founder Fei-Fei Li takes on a new university-wide role as Special Advisor on AI and joins John Hennessy as co-chair of the advisory council.

From left: James Landay, John Hennessy and Fei-Fei Li. Photos: Andrew Brodhead, Linda A. Cicero, Drew Kelly

As AI opens up new opportunities for research and education at Stanford, the university is organizing to meet the moment. Stanford University is merging its two flagship AI and data science organizations into a single institute, to be led by computer scientist James Landay. The Stanford Institute for Human-Centered AI and the Stanford Data Science initiative will combine under the Stanford HAI name, with Landay continuing as Denning Director. University leaders believe the human-centered

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focus is critical to the future of technology. It is reflected in the broad sweep of faculty involved – from engineering to medicine to the humanities and more. Former Stanford president John Hennessy and HAI founding director Fei-Fei Li will serve as co-chairs of the institute’s advisory council. Li will also take on a new university-wide role as Special Advisor on AI to President Jonathan Levin.

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The merger combines HAI’s network of more than 400 scholars, extensive industry affiliates program, and $60 million in cumulative grant funding with Stanford Data Science’s high-performance Marlowe computing cluster and early scholar fellowship program. Levin describes the new Stanford HAI as “the front door for AI at Stanford.” Much of that capacity has been built through donor investment – endowed professorships, the Data Science Scholars program and the HAI Graduate Fellowship program that train early-career researchers, and seed and scale-up research grants funding projects across the university. “The merged organization creates a community of scholars whose research touches powerfully on every aspect of AI, its applications, and implications,” Levin said, “and the humancentered focus provides a north star for the institute.” Landay has spent three decades working in what’s now called human-centered computing. His 1990s design software SILK foreshadowed tools like Figma and Canva; his UbiFit project in the early 2000s anticipated the Fitbit and Apple Watch. In 2024, he received the ACM SIGCHI Lifetime Research Award. “This technology is changing everything,” said Landay, who is also the Anand Rajaraman and Venky Harinarayan Professor in the School of Engineering. “To have real impact in this moment, we need to adapt. This is about shaping how AI affects people, communities, and society – with that human-centered perspective at the core of everything we do.” Opportunities unlocked

AI is beginning to open up research frontiers across the campus. Stanford astronomers use machine learning to spot new exoplanets and model early-universe physics. Neuroscientists build models that predict brain activity. Historians run natural language processing over archival collections to surface patterns in how societies communicate. And education researchers test tutoring systems that adapt to individual learners and support teachers in classrooms. “Data science and AI share the same mathematical foundations and computational infrastructure, each pushing the boundaries of what’s possible with data,” said David Studdert, vice provost and dean of research. “Bringing them

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together under one roof will accelerate research and unlock opportunities that neither of the two organizations could have accessed alone.” Two programs, one roof

HAI, founded in 2019 by Li, former Stanford provost John Etchemendy, computer scientist Chris Manning, and Landay, has grown into a multidisciplinary hub spanning research, education, and policy. It was founded on the principle that Stanford could play a leading role in developing AI technology and applications, and also in leading discussions on what it means to be fully human in an age of machine intelligence. HAI runs the Congressional Boot Camp on AI for policymakers and centers studying foundation models, the digital economy, the science of intelligence, and ambient intelligence for aging in place. It launched fellowship programs for early career scholars, hired junior and senior faculty, developed executive and policy education programs, and produces the annual AI Index. Stanford Data Science, launched and led by Emmanuel Candès, the Barnum-Simons Chair in Mathematics and Statistics in the School of Humanities and Sciences, built out research centers in sustainability, astrophysics, causal science, neuroscience, and other fields; created interdisciplinary graduate student fellowships; recruited faculty members in partnership with collaborating departments; and spearheaded the establishment of the Marlowe cluster. Guido Imbens, the Applied Econometrics Professor and professor of economics at Stanford Graduate School of Business, served as faculty director for the past year and led the transition team with Landay and Li before returning earlier this year to focus on his teaching and research. Candès will become an associate director of Stanford HAI, focused on computational resources. Etchemendy will continue as a senior fellow and advisor. Built on openness

Stanford HAI will organize its work around three pillars: advancing AI and data science for discovery across fields, transforming education from K-12 through lifelong learners, and examining and shaping AI’s societal impact through evidence-based research. This comprehensive approach ensures the university can influence AI development across foundational algorithms, real-world applications, economic analysis, and governance 77

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organizations to extend its human-centered approach beyond Stanford. Landay says Stanford HAI’s defining commitment will be openness: open science, open-source code, open datasets, and open education. Openness has shaped the field before. ImageNet, the labeled image database Li helped create, is widely credited with catalyzing modern deep learning. Open-source code and libraries like FlashAttention democratized AI development. And open science publication subjects results to scrutiny that closed industry work often lacks. “What makes Stanford’s approach impactful is our commitment to operating as an open community,” said Landay. “We publish in open forums, we champion open research, we make knowledge accessible. That’s what differentiates universities from the frontier AI companies dominating artificial intelligence today.” Landay is now working to define what “human-centered AI” means in practice – pressing researchers to design for and weigh impact on users, communities, and society from a project’s inception through to its development, deployment, and maintenance phases.

“This is the most important effort for Stanford, and I am happy to help it succeed,” Hennessy said. “AI will evolve in ways we can’t predict, but the principles guiding our work – openness, excellence, human-centeredness – will be enduring.” Li’s co-chair role is separate from her new university-wide appointment advising President Levin, which will span research, partnerships, education, and student careers across all seven Stanford schools. She will retain her title as Stanford HAI’s founding director and senior fellow. “AI is transforming not only technology, but also the way we pursue scientific discovery, learn and educate, and serve society,” Li said. “It is a historical opportunity and responsibility of Stanford to rise to the occasion.” The new institute will harness team science – spanning Stanford’s seven schools and partners across sectors – to tackle AI’s toughest challenges while preserving what universities do best: pursue fundamental questions, train the next generation, and serve the public good. “This is not just a stronger institute,” Landay said. “It is a new model for how a university organizes AI and data science to have real impact in the world.”

New co-chairs and role

Hennessy, who co-founded the Knight-Hennessy Scholars program, will also serve as a Stanford HAI special advisor, in addition to his role on the advisory council.

“

We publish in open forums, we champion open research, we make knowledge accessible. That’s what differentiates universities from the frontier AI companies dominating artificial intelligence today. James Landay, Denning Director, Stanford HAI

SOURCE

Read the Original news.stanford.edu/stories/2026/05/stanford-merges-hai-data-science Stanford Report, 4 May 2026. Reproduced in TOP Venture format for LP reference.

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Wed 14 Oct

San Francisco

Grey Baker General Partner, Y Combinator

ARTICLE 18

LENNY ’S NEWSLETTER · 11 FEB 2025 · LENNY RACHITSKY & PALLE BROE

Pulling back the curtain on the magic of Y Combinator A first-of-its-kind deep dive into the data to see what’s really working for the industry’s biggest incubator

To honor the final day you can apply to Y Combinator’s firstever Spring batch (i.e. X25), I teamed up with past collaborator Palle Broe on the most in-depth and intriguing analysis you’ll find anywhere of the world’s most successful startup incubator. Palle spent over 100 hours digging through all available public data to answer questions like: 1 How has YC performed over the past 20 years? 2 What are YC’s biggest winners? 3 What impact does joining YC have on your startup? 4 What does YC look for in startups? 5 What is YC betting on most going forward?

Y Combinator (YC) is widely regarded as the most successful startup accelerator and the top choice for world-class entrepreneurs. For those new to the startup world, Y Combinator is like a boot camp for startups. Selected founders receive $500,000 in seed funding in exchange for roughly 7% equity. Four times a year, founders are immersed in a three-month cohort, or “batch,” with about 125 other startups, which are sorted into groups and mentored by successful founders. It’s S T R I C T LY C O N F I D E N T I A L

an exclusive program—with an approximately 1% acceptance rate—offering founders a powerful network, future funding opportunities, and instant credibility. The evidence is clear. Roughly 4.5% of YC companies become unicorns (in contrast to the 2.5% outcome for other venture-backed seed-stage startups), and around 45% of companies go on to raise a Series A (higher than the 33% average). So far, YC has funded more than 90 billion-dollar companies. Top YC companies include Stripe, Airbnb, Coinbase, and Reddit. But what does the data say about the impact of YC and the success of their bets? We tried to demystify the giant by reviewing the 4,939 YC companies so that startup founders, investors, and others can see what’s really going on—and maybe learn from the successes or trends. There was a lot that was surprising in the data. But one theme throughout was that the magic of the incubator appears to be in picking the best founders, understanding trends, and the process within YC, not about repeating the successes of one particular startup profile. Read on to learn more about what we uncovered.

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Image: Lenny’s Newsletter

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Key Takeaways

6 The chances of startup success are higher with YC.

45% secure Series A (vs. 33% average), 4% to 5% become a unicorn (vs. 2.5% average), and 10% achieve an exit.

1 YC has gone from being a Consumer investor to

primarily a B2B investor. Consumer companies have resulted in over $200 billion of market cap, while B2B companies are currently privately valued at some $170 billion and are on the rise.

2 Based on batch profiles, founders are betting on AI

(specifically, B2B AI) to be the next big thing. The most promising subcategories include “Engineering, Product, and Design,” Infrastructure, and Sales.

3 Solo founders are at a disadvantage. Although solo

founders are encouraged, the data does show a steep decline in the number of them accepted to YC.

4 Success has so far been driven by U.S.-founded

companies. More than 70% of the startups have been founded in the U.S., and to date, 99% of returns have come from the U.S.

5 The durability of YC companies is significantly

higher than that of the average startup. More than 50% of companies are still alive after 10 years (vs. 30% average).

7 The investors in YC companies are the “crème de la

crème.” Tier 1 VCs frequently invest in YC companies, and some have made several hundreds of investments.

Sources: Y Combinator, Harmonic, and Crunchbase. Included 4,939 YC startups from the first batch in 2005 (S05) to the fall batch of 2024 (F24). The one-off education-focused batch (IK12) not included. Not considering YC continuity investments. Data is as of December 10, 2024 (or otherwise, as stated on the graphs). Some companies do not disclose valuation or acquisition price, so sometimes the data will not contain all companies. Treat the numbers below as directional, not as exact figures.

What does YC success look like?

Around 10% of YC companies achieve an exit As of today, 17 companies have been backed by YC and gone public. Another 76% are still actively pursuing an exit. But one impressive fact is that only 13% of companies have gone out of business.

High-level stats: the YC startup funnel. Source: Lenny’s Newsletter

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More than 50% of companies are still active after 10 years YC companies are more durable than other startups, which have an average lifetime of around five years. Batch W15, which is now 10 years old, still has more than 50% of its companies actively operating. All other batches since then have more than 50% of companies still operating. Between 25% and 50% of companies get acquired after 10 years A measure of success for any incubator or investor is the number of companies that achieve a liquidity event, either via an IPO or an acquisition. And no one does that better than YC. When you look at the mature batches, we are seeing between 25% and 50% of companies getting acquired. This speaks volumes about the quality of companies in YC. This is in contrast to the 15% of global companies that get acquired if they have raised at least one round of funding. What are the biggest YC winners?

Consumer companies have driven the majority of YC returns By far the largest wins for YC have come through some of their early consumer-focused companies. As a matter of fact, the four companies with the highest market capitalization are consumer companies: Airbnb, Coinbase, DoorDash, and Instacart.

It’s no secret that technology startup outcomes follow a power law distribution, and that is also very much the case for YC, where the top four companies—Airbnb, DoorDash, Coinbase, and Instacart—account for more than 84% of the market value created.

More than $600 billion has been created in market value YC companies attract a lot of funding. In total, more than $145 billion has flowed into the startups that were part of YC. This investment has led to the creation of more than $300 billion in market value, and with the existing private companies, this amount could double to more than $600 billion in the future (once private companies exit). Although acquisitions are the most common path for YC startups, they have “only” brought in $15 billion. Consumer companies top the funding charts as well Cruise and Stripe are the two most well-funded YC companies ever. Cruise requires large amounts of capital due to the expenditures required in the autonomous vehicle industry, and Stripe has been focused on blitzscaling their product globally—also requiring a lot of funding. Two-sided marketplaces such as Airbnb, Instacart, DoorDash, and Rappi are notoriously expensive to get started and require subsidizing one side of the marketplace.

15 most funded YC companies. Source: Lenny’s Newsletter

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Stripe is the next big win for YC Currently sitting at $70 billion in valuation and estimated to go public in the next few years, Stripe is gearing up to have one of the largest-ever outcomes for YC. Companies riding

the AI wave such as Scale AI have seen a rapid increase in valuation and are likely to further benefit from the tailwinds, which could result in even higher valuations in the coming years.

15 most valuable YC companies. Source: Lenny’s Newsletter

Below you can see the capital efficiency of each of these private companies. That is the amount of funding relative to their valuation. Deel, Benchling, and Gusto are showing

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particularly strong capital efficiency ratios.

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15 most capital-efficient YC companies. Source: Lenny’s Newsletter

W09, S12, and S13 remain the best YC batches based on IPOs and acquisitions During Paul Graham’s leadership, YC was fortunate enough to invest in some of the most industry-defining consumer companies. Airbnb, DoorDash, and Instacart were riding the shift to mobile, and Coinbase became the leader in the crypto revolution. Today these are the top companies YC has ever backed based on market cap value. The most promising batches are S09, W17, and W16 When we look ahead, there are some very interesting batches that may soon materialize on the public markets. S09, with Stripe, might overtake Airbnb as the most valuable YC company ever. W17, with Rippling, Faire, and Brex, is also looking exciting. Personally, I believe there is a lot of upside in S16, which is the vintage with Scale AI, one of the hottest AI companies out there now.

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YC has gone from being a consumer investor to primarily a B2B investor Although YC are famous for their Consumer investments (e.g. Airbnb, DoorDash, Reddit, Coinbase), the majority of their funding has actually gone into B2B companies. This is particularly true for their most recent batches, where more than 75% of the companies are defined as B2B companies. The shift away from Consumer is likely driven by the fact that most of the large consumer apps have already been invented. Future returns will be driven by B2B and fintech The best past investments from a returns point of view have been great consumer startups like Instacart, Airbnb, DoorDash, Coinbase, and others. However, looking forward, the large exits for YC will come from B2B and fintech companies with combined valuations north of $270 billion. So far, YC has not had financial success with their investments in Healthcare, Bio and Industrials, or Real Estate and Construction.

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YC returns by sector. Source: Lenny’s Newsletter

By far the majority of investments go to U.S.-based companies It is probably no shock that the largest number of YC-backed companies are based in the U.S. More than 70% of companies are from the U.S., followed by countries such as India, the U.K., Canada, Mexico, and France. So far, 99% of the returns are coming from the U.S. The only meaningful returns have so far come from U.S. investments. There are some promising bets from overseas, such as Razorpay at $7.5 billion (India), Rappi at $5 billion (Colombia), Zepto at $5 billion (India), Meesho at $4 billion (India), and Flutterwave at $3 billion (Nigeria). Slightly surprising is that European-based companies are still lagging behind when it comes to valuations and market cap value. The most valuable European YC company is GoCardless at $2.1 billion.

SOURCE

Solo founders are at a disadvantage There’s a lot of discussion of whether being a solo founder makes it statistically harder to succeed (or get into YC). When Sam Altman was the president of YC, he wrote, “We really prefer at least two founders, but it’s not a dealbreaker.” And the data speaks quite clearly. Over the past few batches, the proportion of solo founders in the batch has gotten smaller and smaller, to around 10% in the latest batches. What is the likelihood of success for YC startups?

40% to 50% of companies that go through YC raise a Series A round

Read the Original www.lennysnewsletter.com/p/pulling-back-the-curtain-on-the-magic Lenny’s Newsletter, 11 February 2025. Reproduced in TOP Venture format for LP reference.

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Thu 15 Oct

San Bruno

Will Aldrich Senior Director of Product Management, YouTube

ARTICLE 19

YO U T U B E B L O G · 5 M A R 2 0 2 5 · LYO R C O H E N

20 years & 125 million subscribers later…

Image: YouTube Official Blog

This year YouTube celebrates its 20th anniversary. From a simple video, we’ve grown into the largest music stage in the world, reaching over 100 countries in 80 languages. We’ve accomplished so much together over the last 20 years… but if you think we’re slowing down, you’re dead wrong. I mean, have you ever heard of anyone retiring at 20? 20 is when things get interesting – when “impossible” and “improbable” don’t yet ring a bell. And it’s with this audacity that we plan to make YouTube the best place for every music fan and every artist. This mission to create the best fan experience fuels a powerful flywheel for artists. Increased discovery, engagement, and community fuel greater promotion and

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monetization opportunities for artists, attracting even more artists and premium content to the platform. The cycle continues and the results are clear: 125 million subscribers: I’m thrilled to announce that with your partnership, we’ve reached 125 million YouTube Music and Premium subscribers globally, including trials – an incredible milestone that many laughed off as impossible when we first launched. This momentum is critical to our goal of becoming the No. 1 contributor of revenue to the industry, and we won’t stop until we get there. Feeding our subscriptions funnel: Today we also announced the expansion of the Premium Lite pilot to US users.

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This more-affordable subscription gives people a new way to enjoy most videos on YouTube ad-free (though users may see ads on music content and Shorts, and as they search and browse). But what’s most exciting is that we believe that Premium Lite can benefit our partners, while giving users more choice. No. 1 in streaming watch time: For 2 years in a row, Nielsen ranked YouTube the No. 1 streaming platform in watch time in the US, with more than 1 billion hours of content viewed daily on TV sets around the world. Our global reach empowers fans to discover new music on Shorts, which now generates over 70 billion daily views, and on connected TVs – the fastest-growing surface for YouTube and the primary viewing device in the US. The trend of artists delivering premium content directly to the big screen continues to grow, whether through music videos or live performances at iconic events like Coachella. In fact, last year more than 50% of Coachella’s live stream viewership was on connected TVs, and we’ll build on that momentum next month.

Now I’m not here just to pat ourselves on the back. There’s still so much work to do. But I’ve never been more bullish about the technology and talent driving YouTube forward. And I believe our commitment to music fans and artists demands we focus on leading the industry in visual storytelling:

SOURCE

The rebirth of the music video: As I look forward, I’m foreseeing a renaissance of the music video. It’s not about having the biggest production budget; it’s about sharing authentic hero content that music fans can’t unsee. It’s about using the artist’s most influential asset – the music video – and cutting through the tidal wave of clutter and choice. Think about the iconic music videos that have shaped our culture. These weren’t simply videos; they were cultural moments. And they didn’t just break songs – they broke artists. The potential of AI: To help bring these visual stories to life across all YouTube formats and surfaces, we also want to make it easier for every artist and fan to create. That’s why we’re investing heavily in AI tools like Dream Screen in Shorts which is now powered by Veo 2, Google DeepMind’s newest state-of-the-art generative video model. With this new integration, artists and fans can create standalone video clips for their Shorts, broadening the horizons to tell visual stories with music.

I know there’s uncertainty in the world and in our industry, but in my 9 years at YouTube and 40 years in the business, I’ve learned that uncertainty and challenges signal great opportunity. I cannot wait to see what the next 20 years of YouTube holds.

Read the Original blog.youtube/inside-youtube/20-years-125-million-subscribers-lyor-cohen YouTube Official Blog, 5 March 2025. Reproduced in TOP Venture format for LP reference.

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ARTICLE 20

YOUTUBE OFFICIAL BLOG · 21 JAN 2026 · NEAL MOHAN

From the CEO: What’s coming to YouTube in 2026 Neal Mohan, CEO, YouTube

Image: YouTube

As we enter 2026, the lines between creativity and technology are blurring, sparking a new era of innovation. This inflection point requires ambitious bets. YouTube is the epicenter of culture. Our creators are reinventing entertainment and building the media companies of the future, and we continue to be the best place for them to grow a business. YouTube has the scale, community, and technological investments to lead the creative industry into this next era. As we look ahead, here are our priorities for 2026: #1: Reinventing entertainment: Creators are the new stars & studios

While technology unlocks new creative possibilities, it’s YouTube creators and artists who are leading the way to reinvent entertainment.

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Our creators and artists

Viewers come to YouTube to immerse themselves in the biggest cultural moments. They want a front-row seat to the Super Bowl action from creators like Jesser and Kay Adams, full red carpet coverage from the Oscars and the immersive fandom experience surrounding a Taylor Swift or BTS album release. We offer it all. YouTubers are buying studio-sized lots in Hollywood and beyond to pioneer new formats and produce beautifully produced, must-see TV. The era of dismissing this content as simply “UGC” is long over. These are shows, built by creators who green-light themselves. Look at Julian Shapiro-Barnum: his upcoming series Outside Tonight is a first-of-its-kind latenight experience built for the digital age. When creators hold the keys to their own production and distribution, the only limit is their imagination.

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Every format on every screen

Whether they're watching on a small screen in their hand or the largest screen in their home, viewers choose YouTube for an unmatched breadth of content: long-form, Shorts, music videos, livestreams, podcasts and more. From niche interests to global trends, viewers are finding what they love on Shorts, which now averages 200 billion daily views. This year we'll bring even more variety to Shorts by integrating different formats – like image posts – directly into the feed, making it easier to stay connected with your favorite creators. We’re also investing in music, whether it's helping you find your next go-to artist, uncovering the stories behind the songs that move you or making it easier to discover and experience new releases. YouTube has been #1 in streaming watchtime in the U.S. for nearly three years, according to Nielsen.1 YouTube is the new TV because creators are the new prime time. Ms. Rachel’s two Children's & Family Emmy nominations prove that creators are defining this next era of entertainment. It’s a powerful start, but we need to see more recognition like this. YouTube TV

Building on our success in the living room, we’re driven by the simple belief that TV should be easy. We’ll soon launch fully customizable multiview and more than 10 specialized YouTube TV plans spanning sports, entertainment and news, all designed to give subscribers more control. YouTube has become the single best destination for viewers who want limitless ways to watch, and we’re proud to build that very best experience for the next generation. #2: Building the best place for kids & teens

Kids and teens rely on YouTube to learn and connect, both inside and outside the classroom. According to a 2025 Kantar survey, 93% of 18-27 year old viewers in the U.S. agree that YouTube helps them learn new skills. And according to a 2025 Oxford Economics survey, 79% of U.S. teachers who use YouTube agree it helps students learn. Our goal is to ensure YouTube remains a place for exploration while empowering parents to guide the journey. When it comes to kids and teens, we have a strong track record of offering age-appropriate experiences, from the launch of the YouTube Kids app in 2015 to a supervised experience for pre-teens in 2021. This year we’ll make it S T R I C T LY C O N F I D E N T I A L

easier for parents to set up new kid accounts and easily switch between accounts, ensuring that everyone in the family is in the right viewing experience. Last week we announced updates to strengthen and simplify parental controls, reflecting our core belief that parents should decide what’s right for their families. Parents will soon be able to control how much time their kids and teens spend scrolling Shorts, including setting the timer to zero (an industry first). This is all in service of empowering parents to protect their kids in the digital world, not from the digital world. #3: Powering the creator economy

YouTube remains the original and largest creator economy. Creators call us home because we offer the most stable path to earn. In the past four years alone, we’ve paid over $100 billion to creators, artists, and media companies. This success fuels economies. In 2024 in the U.S., YouTube’s ecosystem contributed $55 billion to GDP and supported more than 490,000 full-time jobs as creators built businesses and hired employees within their communities. More ways for creator to earn

For every idea a creator dreams up, we provide the business model to match. This year we’ll continue to invest in different ways to earn, from shopping and brand deals to fan funding features like Jewels and gifts. We know these are important revenue streams, especially outside the U.S., for creators like Santiago Matias, who uses Super Chat as a way for fans to influence the outcome of his hit reality series. We’re focused on making YouTube a premier shopping destination because viewers trust product and brand recommendations from creators, like Vineet Malhotra who drove millions of dollars in YouTube Shopping GMV in 2025. With over 500,000 creators already in YouTube Shopping, we’re focused on frictionless commerce. Soon, when a creator like Christen Dominique recommends a product, you’ll be able to buy it without leaving the YouTube app. Accelerating brand deals

Brand partnerships are critical, so we’re making it easier for Influencer Marketing Agencies and brands to find and hire creators, and execute successful campaigns through our creator partnerships hub. We’re also giving creators new tools to make these partnerships successful, like the ability to add a link to a brand's site in Shorts or swap out a branded 89

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segment once a deal concludes, transforming back catalogs into recurring revenue streams. We’re committed to building the most diversified economy in the world – one that turns a creator’s unique vision into a sustainable, global business. #4: Supercharging & safeguarding creativity

For years, AI has been the quiet engine behind our most important innovations, like recommending the next video for you to watch or helping us keep violative content off the platform. To build on this momentum, there are four areas we must get right in 2026: The new creative frontier

Just as the synthesizer, Photoshop and CGI revolutionized sound and visuals, AI will be a boon to the creatives who are ready to lean in. On average, more than 1M channels used our AI creation tools daily in December. This year you'll be able to create a Short using your own likeness, produce games with a simple text prompt, and experiment with music. Throughout this evolution, AI will remain a tool for expression, not a replacement. AI transparency & protections

It’s becoming harder to detect what’s real and what’s AIgenerated. This is particularly critical when it comes to deepfakes. We clearly label content created by YouTube’s AI products, and creators must disclose when they've created realistic altered or synthetic content. Because labels aren't always enough, we remove any harmful synthetic media that violates our Community Guidelines. We’re also building on the foundation of Content ID – a system our partners have

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trusted for well over a decade – to equip creators with new tools to manage the use of their likeness in AI-generated content. Finally, we remain committed to protecting creative integrity by supporting critical legislation like the NO FAKES Act. Managing AI slop

The rise of AI has raised concerns about low-quality content, aka “AI slop.” As an open platform, we allow for a broad range of free expression while ensuring YouTube remains a place where people feel good spending their time. Over the past 20 years, we’ve learned not to impose any preconceived notions on the creator ecosystem. Today, once-odd trends like ASMR and watching other people play video games are mainstream hits. But with this openness comes a responsibility to maintain the high quality viewing experience that people want. To reduce the spread of low quality AI content, we’re actively building on our established systems that have been very successful in combatting spam and clickbait, and reducing the spread of low quality, repetitive content. Transforming the viewer experience

AI will act as a bridge between curiosity and understanding. In December alone, more than 20 million users learned more about the content they watched through our Ask tool, asking questions like “What’s the story behind this song’s lyrics?” or “What ingredients do I need to make this recipe?” We’re also using AI to make more videos accessible. In December, YouTube averaged more than 6 million daily viewers who watched at least 10 minutes of autodubbed content. Ultimately, we’re focused on ensuring AI serves the people who make YouTube great: the creators, artists, partners, and billions of viewers looking to capture, experience and share a deeper connection to the world around them.

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A bet on the future

I’m often asked to predict who the most important creator on YouTube will be in five or ten years. My answer is always the same: it’s someone you’ve never heard of and that person is

“

starting their channel today. And that's what makes me so energized to continue building the stage for this generation and the ones to come. 1. The Gauge report, as of Jan 2026

When creators hold the keys to their own production and distribution, the only limit is their imagination. Neal Mohan, CEO, YouTube

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Read the Original blog.youtube/inside-youtube/the-future-of-youtube-2026 YouTube Official Blog, 21 January 2026. Reproduced in TOP Venture format for LP reference.

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ARTICLE 21

WSJ · 23 SEP 2026 · BEN FRITZ

YouTube Is Battling Netflix Over Top Talent Google-owned platform rolling out better tools for digital producers that could help it keep more of their content exclusively

Image: Noam Galai / Getty Images

Popular digital creators helped YouTube become the world’s dominant source of video. Now it is fighting to keep their loyalty. The streaming platform, which is owned by Alphabet’s Google, faces growing competition from Netflix on turf it has controlled for two decades. The platform known for “Stranger Things” and “KPop Demon Hunters” is writing big checks to lure the producers of shows like “Good Mythical Morning” and “Alan’s Universe” to make Netflix their second home. At an event Wednesday, YouTube is rolling out better tools for digital producers that could help it to keep more of their content exclusively. The company is expected to announce new features for YouTubers who want to make microdrama series, translate livestreams into Spanish, or use artificial intelligence to help edit scripts and videos. S T R I C T LY C O N F I D E N T I A L

“We pride ourselves on the fact that because we’ve created a home for creators, it has created all these other amazing opportunities for them,” YouTube Chief Executive Neal Mohan said of the Netflix rivalry. The fight over creators is yet another sign of their increased importance in the media business, with more viewers just as happy to watch their content as Hollywood studios’ output and advertisers line up to work with them. Fending off Netflix is a tricky task for Mohan because YouTube’s business model is to share advertising revenue with creators, not write big upfront checks. YouTube creators typically get 55% of the advertising revenue

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generated from their videos.

decreased and some have increased.

YouTube has told creators considering a deal with Netflix that it might have a harder time setting them up with lucrative brand deals or giving them time in the spotlight at advertising events like the company’s annual Brandcast.

Tim Katz, YouTube’s vice president of partnerships, said his team is keeping a close eye on those trends internally, so that creators “understand the decisions that they’re making.”

“When you’re speaking to an advertiser, they have to have some understanding about where this content is available and when,” Mohan said. “A creator’s posting strategy has implications.” Netflix’s move into YouTube’s turf began with shows from children’s creators, like “Ms. Rachel,” “Mark Rober’s CrunchLabs” and “Danny Go!” They are now among Netflix’s most popular content with kids. It next moved into video podcasts, another business YouTube dominates, and started recruiting some of that service’s top shows for adults. The deals are typically global and let the creators work with Netflix and YouTube, but not other streaming services. Netflix executives have been looking for ways to reverse a downturn in the amount of time subscribers spend on the service, The Wall Street Journal previously reported. YouTube accounted for 14.2% of streaming video viewing on televisions in the U.S. in July—nearly twice as much as No. 2 Netflix, according to Nielsen. Digital-creator deals potentially increase viewing at a fraction of the cost of premium productions like “Bridgerton.” Other media companies including Amazon.com and Disney have started making deals with creators, but none as aggressively as Netflix. Working with Netflix has had a mixed impact on creators’ YouTube viewership, according to data from Tubular Labs. The strategy firm found some creators’ YouTube views have

SOURCE

YouTube remains the only viable platform for producers making content longer than a TikTok video to build a channel with millions of subscribers. Leaving isn’t a realistic option for most creators, which is why Netflix’s deals call for creators to cross-publish or make additional content on top of their existing YouTube output. At its Made on YouTube conference this week, the company is announcing a new feature that could help creators reach the right audience at the right moment. Viewers will be able to create bespoke algorithms depending on their mood, so they won’t get political commentary when they want comedy. For producers, it is unveiling a tool for one of the hottest genres in entertainment: microdramas. Creators of YouTube Shorts, its TikTok-like vertical video feature, will be able to produce episodic series of videos that stream one after another. YouTube is also launching an AI storytelling assistant that can analyze scripts and rough cuts based on what has worked and what hasn’t on that channel. Another tool will let creators A/B-test videos by publishing different cuts, then take down the one that isn’t performing as well. In addition, live streamers can soon enable live AI-dubbing from English to Spanish—a first step toward automatic translation into many languages. “That’s a way of eliminating what I would argue is potentially the sole barrier between them and new audiences today,” said Mohan.

Read the Original wsj.com/business/media/youtube-is-battling-netflix-over-top-talent-eebbf0cf The Wall Street Journal, 23 September 2026. Reproduced in TOP Venture format for LP reference.

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