Show notes
In this episode, Corey Quinn sits down with Dexter Horthy, CEO and Co-founder of Human Layer, to unpack what engineers are getting wrong about AI, especially when it comes to coding agents.From the obsession with “just throwing more tokens at the problem” to the reality of building scalable AI workflows, Dexter shares hard-earned insights on how to actually push models to their limits. They dive into the evolution of developer workflows, the rise of AI-powered software factories, and why understanding context and verification matters more than raw model power.If you’re building with AI or trying to, this episode will challenge how you think about what these systems can (and can’t) do.Show highlights: (00:00)Throwing Tokens Too Far(01:04) Meet Dexter Horthy(01:52) Personal AI Benchmarks(04:12) Human Layer Race Condition(05:59) Rewrites and Tech Debt(07:19) Software Factories Mindset(10:20) Verifiable Problems and Token Limits(13:45) Agents in the Trenches(18:05) GitHub at Agent Scale(26:23) Safety Ethics and Closing ThoughtsAbout Dexter: Dexter Horthy is the CEO and Co-Founder of HumanLayer, where he helps engineering teams tackle complex problems in large codebases using coding agents. Previously, he worked in DevOps, SRE, and Solutions Engineering at Replicated, and contributed to lunar navigation software at NASA JPL. Outside of work, he’s a fan of tacos and burpees, though not necessarily in that order.Links: LinkedIn: https://www.linkedin.com/in/dexterihorthy/Website: https://humanlayer.devSponsored by: duckbillhq.com
