AI: A 100x Force Transforming Our Lives
AI + Human = Human²

We are living through a sea change in how we use software to navigate our world. We can now chat with it using English or our native language. It can go beyond processing to thinking or reasoning. As a result, artificial intelligence can become intelligent augmentation, liberating us to forge new relationships and adopt innovative behaviors.
We are technology optimists at Mayfield. Our view on AI can be summarized as AI + Human = Human², as in Human Squared. We believe that AI teammates will work alongside humans to automate tasks, accelerate productivity, augment capabilities, and amplify creativity, advancing humans to superhuman levels. As a result, we will see the rise of a new hybrid workforce, with AI teammates for every business persona.
Having lived through multiple paradigm shifts, we have identified the model through which AI will be delivered and consumed, which we have named Cognition-as-a-Service (CaaS). This follows prior mega waves of IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service) and SaaS (Software-as-a-Service).
Our AI focus is on all six layers of the CaaS stack - semiconductors/infrastructure, models, data, middleware, applications and teammates. We refer to the bottom four layers as cognitive plumbing which are the technologies required to build AI enabled apps and agents/services.
With AI optimism as our foundation, CaaS as our thesis, the cognitive plumbing layer as our primary focus, $1.2 billion in available capital across three funds, conviction on leading rational financing rounds, and with a proven craftsperson approach to early stage investing, we have built a vibrant portfolio of 20+ companies which are well capitalized and executing on their missions.
We have been advocating our POV with our community of founders, CXO/enterprise buyer leaders, technology luminaries, academics and researchers, peer investors, and the press. Our POV along with our reputation as a firm built for founders, by founders, who partners with founders for life, has resonated with many extraordinary founders. We are looking forward to partnering with them to build enduring companies that establish AI as a ubiquitous force for good.
Every day, we are seeing AI elevate our lives by automating our daily tasks and augmenting our capabilities. We are bullish about the concept of AI teammates, intelligent pieces of software, which are built using Large Language Models. These teammates allow humans to interact with them via natural language, and are able to research, plan, and take action to complete daily tasks. In business, this is going beyond content creation and code generation to fundamentally transform essential enterprise workflows. Our company Sema4 has developed an automation-as-code platform that builds AI teammates that go all the way from intent to action. For example, a bank manager can go beyond simply chatting with an LLM (if they’ve implemented one) on what to do in the case of a fraud alert to actually taking action on blocking the transaction and sending the customer the recording and remediation forms. It’s only a matter of time before AI teammates for every persona are available, creating a cadre of digital co-workers who work alongside humans to not only automate mundane tasks, but to also complete higher-level intelligent tasks that could previously only be done by humans. On a consumer level, whimsical examples of assistants that sort your laundry or design stickers are being discussed. We’re all hoping to simplify our travel — imagine AI finding you a perfect beach for a specific number of people, booking your hotel and flight, remembering to ask if you need a car or two, recording and communicating your diet preferences, checking you into your flight, and delivering your boarding pass. We see a future where every persona gets a digital co-worker, enabling humans to behave like superhumans.
AI may not be coming for your job anytime soon, but it surely is coming to work alongside you.
Introducing your new teammates: Devin, the AI software engineer; Hippocratic, the AI healthcare worker; Outreach Kaia, the AI sales assistant; Evenup, the AI legal assistant; and Hawkeye, the AI ITOps engineer. Reflecting on conversations with hundreds of entrepreneurs, we’re witnessing a shift from Automation to Augmentation. Artificial intelligence isn’t about replacing humans; it’s about augmenting intelligence. In this new era, AI liberates us to forge new relationships and adopt innovative behaviors. Despite fears of AI replacing humans, we recall the discussion about offshoring two decades ago. Then, as now, there were concerns about the impact of technology on humans. However, unlike the offshoring wave, we firmly believe AI teammates will not only boost productivity but also enhance, amplify, and elevate human capabilities.
Take Hawkeye, unveiled by NeuBird. An e-commerce company may notice that its website is performing poorly at populating shopping cart suggestions. Traditionally, this would require assembling a cross-functional team involving IT, web developers, and data analysts to investigate the issue, a process that can be time-consuming and resource-intensive. Using NeuBird, the same company can simply ask: “Why is my website running slow?” and “How can I resolve that?” NeuBird’s Hawkeye will diagnose the issue, contextualize potential reasons for the problem, share steps needed to resolve it, and even write code to fix it. This frees ITOps engineers to assist a great number of customers and tackle more complex issues, showcasing the power of AI-human collaboration. Welcome to the era of AI teammates. Together with humans, they automate tasks, accelerate productivity, augment capabilities, and amplify creativity, advancing humans to superhuman levels.
The Plumbing Layer Rises Again.
Mayfield’s conviction in infrastructure investmenting began 25+ years ago. We’ve been a believer in the power of plumbing to help consumers and businesses realize the benefits of technology waves. During the Web era, Navin joined a long line of tech industry school dropouts to co-found his first company in 1996 with his PhD advisor at Stanford University. VXtreme made it possible to stream video over the Internet, and after its acquisition by Microsoft, endures as Windows Media. While at Microsoft, Navin invested in Akamai, which delivered infrastructure to scale the Web.
In 2014, as the cloud era got into full swing, Mayfield partnered with Armon Dadgar and Mitchell Hashimoto, the open source superstar founders of HashiCorp, whose mission was to elevate the devops professional with a simple and comprehensive multi-cloud infrastructure platform. HashiCorp’s public offering in December 2021 valued the company at $15 billion, and it continues to power major cloud-based businesses today. Over the last decade, we have partnered with many bold enterprise founders including those at CloudSimple, CloudGenix, Elastica, Gigya, Portworx, NUVIA, Rancher, StorSimple, and Volterra who successfully realized their mission to cloudify the world.
As AI shifts from early adoption to widespread enterprise use, the importance of the “plumbing layer” is resurgent. The transformative potential lies in four layers of the tech stack: models/middleware/tools, data, infrastructure, and semiconductors/systems. The breakthrough of GenAI is in elevating humans by providing a natural language interface and performing cognitive tasks — an era we think of as AI+Humans = Human Squared. In this context, cognitive plumbing unlocks the easy creation of agents, applications, and services that can be built on this foundational technology. In the future, we’re looking forward to partnering with many more cognitive plumbers of the AI age.
DATA
One company in stealth
One company in stealth
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Two companies in stealth
It’s hard to overstate the impact that artificial intelligence (AI) is going to have on every aspect of business and the economy. In the tech industry, we have long understood its potential. Much of the rest of the world woke up to its transformational power more recently, particularly following last year’s launch of ChatGPT. Naturally, that awesome power has raised a slew of questions. What are AI’s potential benefits and downsides? Will the former outweigh the latter? What will AI do to productivity and jobs? Will it exacerbate inequality? Where is it going to take us? Will we be able to control AI, or will it control us? Each of these questions merits a healthy debate.
As a veteran of the tech industry and as an investor whose firm’s motto is “people first,” I bring an unabashedly optimistic perspective to the conversation. But optimism doesn’t mean complacency. Everyone in business – from the startups creating AI technologies, to the companies adopting machine learning algorithms to supercharge their products or operations – has a role to play in ensuring AI is truly a force for good.
Here’s why I’m optimistic, and what I think companies big and small should be doing today to ensure a positive outcome.
Those of us who have been around the tech industry for years have seen it again and again – powerful emerging technologies raise fears about jobs. And certainly, new forms of automation eliminate some jobs. But they also create efficiencies and streamline repetitive tasks, allowing humans to move up the value chain.
Ultimately, more jobs are created. Personal computers, for example, eliminated some jobs for typesetters but helped to create far more employment through desktop publishing. I am convinced that AI will have that kind of effect, but on a much larger scale. It will create massive productivity gains that will allow businesses to invest more, innovate more and generate new jobs along the way.
But that’s just one part of the story. I also believe AI will give us new superpowers that will make our work more satisfying and our lives richer, leading us into an era I think of as “human squared.”
How? First, our way of interacting with technology will change. Going forward, our primary way to communicate with computers will be through rich and layered conversations. Perhaps more importantly, for the first time, technology will be able to perform cognitive tasks that augment our own capabilities.
Rather than merely speed up and automate repetitive tasks, AI will generate net new things much like humans do. The result is that we’ll be able to multiply our own capabilities with a human-like assistant. Whether you call it an intelligence agent (AI becomes IA), copilot, teammate, coach, genie or something else, it will make us immensely more capable, regardless of the task we are performing. I believe that we are witnessing a whole new layer of cognitive plumbing that is being built to drive this wave.
The entrepreneurs creating tomorrow’s AI systems and applications all face choices in how they develop and harness the technology. That’s why, as an investor in startups, I encourage all founders to build trustworthy companies from day one. What do I mean by that? One of the first things I do when I meet founders is to probe their values. I want to know whether they are driven by human-centric mission, and whether their vision for how to deploy technology is aligned with ours.
These are probing and broad ranging conversations that inevitably cover a few key topics:
Trust and safety can never be an afterthought. In the past year, the potential pitfalls of AI – whether it is hallucinations, lack of transparency, inequity, bias, deep fakes, copyright infringement or other issues – have been well publicized. If AI is going to be a force for good, founders must not only be aware of them but also determined to address them. They must evaluate the trustworthiness of the models they develop and use, and ensure that they are compliant with a nascent but rapidly growing regulatory regime.
Data privacy is a human right. AI is fuelled by data and companies should treat that data responsibly. That means not only complying with regulatory regimes, but also embracing ethical practices around its use. That ranges from transparency about what they will and won’t do with it, to the handling, classification, and security of sensitive data, and the careful inventory, lineage, retention and consent to use of everything that goes into AI models. The time to put guardrails around data practices is now, not after breaches or privacy violations are exposed and it’s too late to prevent harm.
Startups should not only dedicate themselves to AI safety, accountability, and averting harms, but also state their commitments publicly, as, for example, Anthropic has done, which should serve as a model for others to emulate.
Just like the companies creating AI technologies, those that are deploying them have choices to make and, I would argue, a duty to do so responsibly. I’m encouraged by what I’m seeing and hearing.
Whether it’s through our annual survey of CIOs (chief information officers) or in conversations across the industry and at events like the World Economic Forum’s Annual Meeting in Davos, I have noticed a sense of collective urgency among many business leaders to do the right thing.
But that’s easier said than done. Implementing responsible AI practices across an organization is a challenge that requires resources, commitment and leadership. Like anything in business, it must begin with an adequate budget and a mechanism for accountability.
The person or group that oversees it needs to have the visibility and stature within the organization to be able to convene stakeholders – across tech, legal, compliance, audit, and other functions – and influence decisions. Importantly, the CEO and board should know how those groups are working together and the roles each has to play.
Some companies are waiting for regulatory regimes to force their hand. I think that’s a mistake. Deploying AI responsibly, and doing it in a way that doesn’t slow the pace of innovation, is not like flipping a switch.
Those who aren’t laying out thoughtful plans today are already behind. For those who don’t know where to start, a growing number of certification programmes from organizations like the Responsible AI Institute can help lead the way. The time to do so is now.
AI is already improving our economy and wellbeing in myriad ways, including higher worker productivity, more accurate health diagnoses, new forms of drug discovery, and better decision-making, to name a few. But that’s just the beginning.
I am certain that businesses and entrepreneurs will be able to harness AI technology in new ways that will unlock untapped human potential and benefits on an unprecedented scale. We just need to approach innovation with the right motivations and accountability mechanisms to ensure that promise becomes reality.
AUGUST 30, 2023
Today marks nine months since ChatGPT was released, and six weeks since we announced our AI Start seed fund. Based on our conversations with scores of inception and early-stage AI founders, and hundreds of leading CXOs, I can attest that we are definitely in exuberant times.
In the span of less than a year, AI investments have become de rigueur in any portfolio, new private company unicorns are being created every week, and the idea that AI will drive a stock market rebound is taking root. People outside of tech are becoming familiar with new vocabulary. Large language models. ChatGPT. Deep-learning algorithms. Neural networks. Reasoning engines. Inference. Prompt engineering. CoPilots. Leading strategists and thinkers are sharing their view on how it will transform business, how it will unlock potential, and how it will contribute to human flourishing.
While there are still many unknowns, and it is prudent for us to be aware of the risks as well as the potential of any new technology (“Oppenheimer,” anyone?), one firm conviction makes me optimistic. We are guided by a “people-first” philosophy at Mayfield, one in which the startup founder’s bold vision elevates the customer of their product and ignites a community. When applied to AI, people-first has even more powerful resonance. I believe that two dynamics will combine to establish AI as a powerful force that will allow any human to become what I call Human2 — as in, “human squared.”
First, our main form of interacting with computing devices will change. It will become conversational. Whereas we once relied on a command line, then the GUI, the browser, and the mobile device, we are now going to primarily communicate with computers through rich and layered conversations. The impact of that change will be compounded by a second one: For the first time, technology will be able to perform cognitive tasks that augment our own capabilities.
Rather than merely speed up and automate repetitive tasks, AI will generate net new things much like humans do. The result is that we’ll be able to multiply our own capabilities with a human-like copilot — or teammate, or coach, or assistant, or genie. AI x Human = Human2. And precisely because the potential and power of AI is so great, the need to focus on responsible development is paramount.
We have customized our people-first framework to apply to AI companies and are using it to guide our investment decisions. Today, we are publishing the five key pillars of that framework in the spirit of fostering responsible AI investing:
Founding values drive culture. They are not something that can be bolted on as a company grows. We saw this in the missions of three of our most successful companies over the last decade. Lyft was dedicated to improving people’s lives with the best transportation; Poshmark put people at the heart of commerce, empowering everyone to thrive; HashiCorp built critical infrastructure that allowed others to innovate. This time around, we are having similar discussions with AI-first founders to see if they have a human-centric mission and authentic values. We want to understand what drives their thinking about the impact of their technology and ensure we’re aligned.
The recent explosion in AI has been driven by innovative thinking by researchers, model builders, ethicists, and technologists. We believe that founders who have been steeped in that world understand how to design and build people-first AI businesses.
So when we meet with founders, we are looking for:
• A fundamental belief that AI will augment humans, not replace them — AI is a teammate or even a co-founder.
• A founding team that has worked in the academic or applied generative AI field, or one that has a unique insertion point into the generative AI wave.
• A passion for design and user experience to bring out the invisible AI capabilities to all human-computer interaction and workflows.
• Solutions that are powered by generative AI elements like LLMs, proprietary models and datasets, and a chatlike natural language interface.
• An overall value proposition that involves the cognitive offloading of repetitive tasks.
As we already know, there are some harmful effects of AI. Some we have identified include hallucinations, poisoning, lack of transparency, inequity, injustice, bias, deep fakes, IP and copyright infringement, and violations of privacy and security. We are asking founders to evaluate the trustworthiness of the models driving their innovation, and encouraging them to look at pioneering work on holistic model evaluation such as that being done at Stanford. We believe founders need to evaluate this not only at the time of model selection but also in the whole lifecycle of a model, from development, to testing, and deployment. At the same time, compliance with the growing regime of regulations, guidelines, and frameworks for the responsible use of AI is paramount.
We believe that privacy requires its own focus and cannot just be subsumed under trust and safety. Fortunately, given the myriad of regulations like CCPA, DGA, DMA, DPA, GDPR, PIPA, and PDPO that emerged in recent years, companies are already working on putting data controls in place. This is especially important in the age of generative AI, when models produce new data from training sets, and the unauthorized use of training data has become a significant intellectual property concern. Regulations for the ethical use of data, which provide assurance and risk management, are now emerging across the globe.
Governance areas that have to be addressed include discovery and inventory of all data; detection and classification of sensitive data; understanding models’ access and entitlements by users; consent, legal basis, retention, and residency understanding; and quality and lineage.
Paying attention to these things is critical. We are asking founders to do so and encouraging them to build guardrails now. It will be too hard to act once the proverbial data horse has left the barn.
We believe that people-first AI will truly elevate humans, and we are working on a design framework to measure that potential when meeting founders. Going back to our company examples, Lyft, Poshmark, and HashiCorp elevated drivers, seller stylists, and cloud practitioners, respectively, enabling them to grow into vibrant communities. They had to make tough decisions to stick with their commitment but ultimately were rewarded by the satisfaction of having achieved their missions of empowering and elevating people.
As an inception and early-stage investor, our focus is to champion entrepreneurs and help them build iconic companies. We believe that bringing a people-first approach to fostering generation-defining AI companies will result in enduring companies and a richer, better world.
Keynote
BY NAVIN CHADDHA1
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Company building is a team sport with shared values Sell painkillers, not vitamins, to a substantial market
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Find your differentiation and build a deep moat Trusted founder-investor relationships are a two way street The road from unicorn to unicorpse can be short & swift
Jensen Huang, CEO of NVIDIA
How hard can it be – the question I ask myself when faced with a situation.
Ignorance can be a superpower –don’t share everything you have learned with your younger self.
AI is a natural resource and data a national treasure. All countries should develop sovereign AI.
With a set of core beliefs, Jensen says you need to test assumptions and if facts change, then your mind needs to change as well. This informed their thinking on one of their toughest decisions – to swap out an architecture that was based on a palette of technology choices that was wrong. While this was at a time when the company was young and fragile, by keeping in mind that the purpose of the company superseded a single choice, NVIDIA navigated through the transition and has never looked back.
We advise entrepreneurs to build deep moats, which Jensen thinks of as having a different perspective. While there were several vendors who were building graphic processors, NVIDIA was the only one that was thinking about applications and building a full stack accelerated computing platform. By combining this with the nurturing of a rich developer ecosystem, which has expanded into their Inception program for startups today, NVIDIA is guided by a model where it succeeds only if others succeed.
Jensen is a rare CEO who has 60 direct reports. He pointed out how prior models of leadership were drawn from the battlefield, where only the general makes strategic decisions, while the foot soldiers fight on the ground. He believes that information flow has to be high in companies, and is proud of the world class experts who report to him, along with one person whom he just congratulated on their 30th anniversary!
Jensen sees AI as the 4th Industrial Revolution, following the steam engine, electrons/AC power, and software. He discussed how AI factories can produce intelligence at scale, which resonated with me as we are seeing how AI is being delivered and consumed using Cognition-as-a-Service (CaaS) as the model. His view on AI sovereignty is unique. He sees that a nation’s wealth extends beyond the natural resources buried beneath the ground with data as a national treasure. He believes that every country possesses the right to harness and capitalize on the potential of its own data to drive economic growth and societal advancements.
What is Cognition-as-a-Service (CaaS)?
What is Cognitive Plumbing?
What We Look for in Founders
Episode 1: Building Trust with Your Inception Investor
Episode 2: Digging Your Moat: Customer Discovery + PLG for AI Startups
Episode 3: Tapping into the AI Developer Community
Episode 4: Fundraising from Both Sides of the Table
Episode 5: Breaking into Enterprise Sales
Episode 6: Understanding Privacy and Compliance
Episode 7: Communicating Your Vision
Episode 8: Scaling to $1M ARR and Beyond
Episode 9: How to Take Your AI Startup from Research to Reality
Episode 10: Enduring Strategies for Inception-Stage Founders and Investors
Presented at NVIDIA GTC and AI Fund
Mayfield has built a global network of C-level executives and business leaders from across all industries, who need access to new ideas to compete in their own markets. This is a highly engaged global network whose members engage with our portfolio, join our events, and provide their own top of mind priorities in formal reports.
Mayfield has built close alliances with leading AI-focused seed funds to co-invest and mentor ideation stage founders.
Each year Mayfield completes a comprehensive CXO survey based on the pressing topics of the day. In 2024, that topic was of course generative AI, and how it’s beginning to push the boundaries of human ingenuity, reshaping industries at an unprecedented pace. In this dynamic environment, IT leaders face the critical task of aligning their AI and IT priorities to navigate the digital frontier and ensure their organizations thrive.
We host quarterly educational calls designed specifically for our network of CXO practitioners. These calls are a chance for us to dive deep with our community into a range of relevant topics that shape today’s tech landscape, equipping executives to tackle both technological advancements and pressing business challenges. Recent calls have included topics ranging from early AI use cases in the enterprise today, to how to effectively score and implement early AI initiatives.
Even before ChatGPT, one-third of CIOs say their organization had already deployed artificial intelligence (AI) technologies, and 15% more believed they would deploy AI within the next year, according to the 2023 Gartner CIO and Technology Executive Survey. But deciding how best to proceed means factoring AI into business value, risk, talent, and investment priorities. As a next step, CIOs and other organizational leaders must create an AI strategy roadmap that synthesizes the enterprise’s vision for the future: outlining potential benefits, while mitigating risk, capturing KPIs, and implementing best practices for value creation. We speak to leading CXOs across a variety of industries to learn more about how they are enabling a technology-driven transformation for the business.