Sarah Guo - What the 250 People Building AI Believe - [Invest Like the Best, EP.489]
Sarah Guo, founder of Conviction venture capital, discusses her investment strategy focused on the 250 frontier researchers and entrepreneurs shaping AI, her approach to identifying extraordinary people and teams, and her concerns about compute infrastructure, regulatory hurdles, and maintaining Western technological independence in an increasingly competitive global AI landscape.
Summary
Sarah Guo explores what it takes to be a successful early-stage investor during AI's explosive growth. She emphasizes her belief in the 'great man and great woman theory of history'—that exceptional individuals with proper capital and support can genuinely alter outcomes, citing examples like Sunday Robotics founders Tony Zhao and Cheng Chi who she believes have contributed most major robotics AI ideas in the past four years. Guo describes her investment decision-making process as highly instinctive about people but rigorous about understanding domains, often starting at an 8 or 9 conviction level and then working backward to identify gaps in her judgment. She's built Conviction around the concept of identifying and supporting roughly 250 frontier people—researchers, entrepreneurs, and builders pushing forward the most interesting work. Her time allocation skews heavily toward portfolio company support (60-65%), with the remainder split between evaluating new companies and ecosystem learning. On the broader AI landscape, Guo expresses concerns about compute infrastructure as the critical bottleneck. She notes that natural gas, nuclear power, and data center construction face regulatory rather than technological constraints, and that America's ability to build at scale has become the limiting factor. She's invested in nuclear energy, alternative chip architectures, robotics labor solutions, and data center infrastructure to address this gap. Regarding open-source AI models, Guo argues the cat is out of the bag and that attempting to restrict open-source models in the US would only handicap American businesses while not affecting actual adversaries. Instead, she advocates for rigorous safety testing rather than speculative restrictions. On investment philosophy, Guo advocates for genuine conviction based on first-principles understanding rather than pedigree proxying, though she acknowledges the tension between backing exceptional people even when you don't fully understand their specific domain. She discusses her shift in conviction regarding biology, moving strongly toward the belief that AI models can create enormous value in drug discovery and R&D acceleration, contrary to conventional biotech wisdom. The firm's name, Conviction, reflects her belief in taking non-obvious positions with full commitment based on asymmetric information and insights others haven't yet adopted. Guo emphasizes her parents' entrepreneurial legacy, particularly their emphasis on integrity, independent thought, and the moral imperative not to worry about others' opinions. She's notably enthusiastic about positive-sum, collaborative approaches to building, contrasting with what she sees as unnecessary zero-sum competition in traditional venture structures. Looking forward a year, she predicts widespread adoption of AI agents and products that automate mundane work across all domains, following the pattern already visible in software engineering, leading to increased productivity and the need for workforce education and adaptation.
About this episode
My guest today is Sarah Guo, founder and managing partner of Conviction, the venture firm she built to back AI-native companies from their earliest days. Sarah has become one of the most sought-after early-stage investors in AI, often the first check into the companies defining the frontier. In this conversation, we go inside that frontier: what the small group of people actually building AI believe right now, why some of the field's best researchers are wrestling with their own sense of purpose, and how close we are to robots in the home and a genuine acceleration in scientific discovery. At the center is Sarah's conviction that no single company will own the future of AI, and what that means for founders, investors, and anyone allocating their time and resources in a world moving this fast. Our managing editor Dom Cooke wrote a profile of Sarah for Colossus, "Sarah's Wager," on how she built the firm closest to the AI frontier and why she's now betting against its biggest companies. Please enjoy this conversation with Sarah Guo. For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at colossus.com/subscribe. ----- Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, Vanta continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to vanta.com/invest. ----- WorkOS is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit ridgeline.ai. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like the Best (00:02:16) Investing Without a Backtest (00:03:31) The AI Wager (00:06:16) Building the Best Investment Firm (00:08:37) Finding Non-Obvious AI Opportunities (00:11:00) The Frontier AI Talent Race (00:13:50) Compute as the Constraint (00:19:10) The Future of Robotics (00:22:15) Making Investment Decisions (00:26:13) How Sarah Spends Her Time (00:28:15) Raising a Venture Fund (00:30:49) Lessons From Her Parents (00:34:38) The Case for Open Source AI (00:39:01) Abundant Intelligence Isn't Inevitable (00:40:55) Compute Independence (00:43:14) Debates Inside Conviction (00:45:27) AI's Opportunity in Biology (00:48:58) Why Conviction (00:50:31) Finding Truth and Taking Risk (00:54:16) What Changes in the Next Year (00:56:46) The Kindest Thing
Key Insights
- Guo believes individual researchers and entrepreneurs with proper capital and network support can meaningfully alter outcomes in AI development, citing specific examples of founders whose ideas now dominate their domains.
- She starts investment decisions at high conviction (8-9 out of 10) based on instinct about people and fundamental understanding, then works backward to identify gaps in her judgment rather than building conviction slowly over time.
- The primary constraint on AI progress is not technological capability but regulatory approval and financing for energy infrastructure (natural gas plants, nuclear power, data centers), which America is struggling to build at necessary scale.
- Open-source AI models from China, Europe, and the US have already become competitive at frontier performance levels; attempting US restrictions would only handicap American businesses while not affecting actual adversaries who operate outside legal frameworks.
- She has fundamentally shifted her conviction in biology from believing AI-based pharma platforms cannot generate venture-scale returns to strongly believing they can create enormous captured value through R&D acceleration with top pharma companies.
- Many frontier researchers at major labs now feel disempowered by the narrative that either compute scale alone matters or that their individual contributions don't matter, which is psychologically unhealthy for the ecosystem.
- Investment decision-making should be grounded in genuine first-principles understanding of business logic rather than proxying judgment to founder pedigree or following other investors, even for exceptional people.
- The firm's name 'Conviction' reflects the ability to hold non-obvious market positions with full belief until proven true or false, aligned with taking asymmetric information seriously rather than following dominant narratives.
Topics
Transcript
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