About Thomas Smith
Thomas Smith is a San Francisco Bay Area-based AI and search visibility consultant focused on the intersection of SEO and Generative Engine Optimization (GEO) -- helping brands earn citations, recommendations, and qualified traffic from AI-powered discovery (ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews) while still winning in traditional search.
A graduate of Johns Hopkins University (Cognitive Science/Neuroscience and Anthropology), Thomas has spent 15 years working across AI, content, and publishing.
He is the Co-Founder and CEO of Gado Images, an AI-driven photography agency and social enterprise, and the Editor-in-Chief of the Bay Area Telegraph, where he runs a high-output newsroom and content operation that lives or dies by search performance.
Thomas is also a longtime writer and editor covering AI and AI search. He is a contributing author at Fast Company (including a weekly column on generative AI and GEO topics), and the founding editor of The Generator, a publication focused on generative AI news, analysis, and real-world testing.
Smith serves on the AI and Search Working Group of the Digital Media Leadership Alliance (DMLA). He routinely speaks and consults on GEO and SEO topics for private clients worldwide.
The Three Pillars of GEO (Thomas' core system)
Most "AI optimization" advice is either too abstract to execute or too tactical to scale. Thomas' work is built around a simple, durable framework -- the Three Pillars of GEO:
1) Technical (Clarity and Crawlability)
Generative engines still rely on web fundamentals. If your site is blocked, confusing, or inconsistent, AI models either ignore you or hallucinate details. This pillar focuses on crawl access (including robots controls), clean information architecture, and machine-readable signals (like structured data and schema) that reduce ambiguity.
2) Content (Answer-Ready Coverage)
GEO is not "more content" -- its content that is structured to be used in answers. That means precise definitions, consistent entity naming, strong sourcing, editorial formatting that makes extraction easy, and topic coverage that matches real customer questions across the full journey.
3) Brand (Authority and Trust Signals)
AI systems weigh what the broader web "agrees" is true. This pillar strengthens the signals that make your company safe to cite: credible third-party mentions, aligned profiles, expert positioning, reviews, and visibility in the places models learn from and users trust.
Together, these three pillars turn GEO into a repeatable operating system -- not a one-off experiment.
Speaking and field experience
Thomas regularly speaks and consults on GEO, including sessions on "SEO, AI & the Future of Search" for industry audiences and marketing podcasts focused on the shift from search to AI answers.
AI Background
Thomas has served as an OpenAI beta tester and has been cited by the New York Times as a "veteran programmer" in coverage related to AI-generated code, reflecting his long-running, hands-on work with human-in-the-loop AI systems.
Smith holds a degree in Cognitive Science (Artificial Intelligence, Neuroscience and Linguistics) from Johns Hopkins University.
