Dean Skira Challenges the Lighting Design Process At a recent VLDC session during Light + Building, Dean Skira stepped onto the stage and addressed a topic the lighting industry has wrestled with for decades: light pollution. Rather than revisiting familiar critiques, Dean offered a fundamentally new way of thinking about how we design light in cities. “We all talk about AI lately,” Dean began, acknowledging how artificial intelligence has quickly become part of everyday life. From email filtering to autonomous vehicles, AI is already embedded in modern systems. Yet, as Dean pointed out, the lighting industry has been slower to harness its potential in a meaningful way. What followed was a challenge to long-standing industry practice.
Rethinking the Urban and Street Lighting Design Process Dean argued that the industry’s current workflow is backward. Today, manufacturers develop luminaires first. 74
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Designers then use those predefined products to calculate lighting levels and apply them across projects. “This is the opposite way,” Dean explained. “We should calculate first.” Instead of starting with a fixture, Dean proposes beginning with the environment itself—defining the exact lighting needs of a specific space before any product is selected. Only after determining optimal illumination levels should luminaires be designed or chosen to meet those precise requirements. The implications are significant. Cities are not uniform. A residential street, a city park, and a public plaza each require different lighting responses. Yet too often, similar luminaires are applied across vastly different contexts. “We cannot treat the residential area and commercial area the same,” Dean emphasized.
Introducing Taman To address this disconnect, Dean introduced Taman, an AI-driven software platform developed over several years.