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Ion Stoica, UC Berkeley professor and co-creator of Apache Spark, Mesos, and Ray, turns academic systems into commercial infrastructure through Databricks and Anyscale, illuminating open-source economics as computing shifts from big data toward distributed AI.
Eiso Kant, builder of source{d}, Athenian, and Poolside, treats software development as a path to artificial general intelligence while giving engineering leaders concrete models for reinforcement learning, actionable team data, and daily high-functioning operations.
Douglas Chen, technical co-founder of Windsurf, formerly Codeium, scaled an AI-powered IDE beyond a million users before its Google DeepMind acquisition. His “dehydrated” hiring philosophy ties lean teams, hard pivots, and agentic tools to measurable product utility.
Daniel Gross, software engineer and investor, co-founded Cue, directed machine learning projects at Apple, served as a Y Combinator partner, and co-authored Talent. His frameworks connect interviewing and human-capital judgment with practical baselines for building software and teams.
Calvin French-Owen, co-founder and former CTO of Segment, documents the engineering judgment behind early validation, architectural scale, and leadership transitions, including Segment’s debated retreat from microservices and his subsequent work building Codex at OpenAI.
Brett Adcock, founder of Vettery, Archer, and Figure, argues that physics can make hardware more tractable than software and that massive problems attract elite talent, linking those convictions to deep-tech scale, capital, and an automated physical economy.
Aravind Srinivas, co-founder and CEO of Perplexity AI, combines reinforcement-learning experience at DeepMind and OpenAI with a focus on answer engines, examining execution speed, model limitations, human curiosity, and the mechanics of discovering knowledge.
Andy Konwinski, co-founder of Databricks and Perplexity AI and contributor to Apache Spark and Mesos, studies how academic research becomes commercial software while open-source development, product strategy, and geopolitics shape the future of AI.