Andrej Karpathy says the goal is to maximize how long an agent runs without your intervention. But there’s a false summit most teams hit first: individual speed goes up while system speed stalls, laptops roar under four parallel Gradle builds, and review queues keep growing. Kaushik and Iury trace the full arc — from local multitasking to cloud-hosted async work to fully autonomous agents that fire on repo events and send you PRs to approve.
2026
The hard part of AI coding isn’t generating code — it’s controlling quality, safety, and drift. Drawing from OpenAI’s Codex case study, Mitchell Hashimoto’s post on AI workflows, Stripe’s Minions project, and real-world experience, Kaushik and Iury break down harness engineering: the five pillars for shaping an agent’s environment, and what it looks like when teams build custom harnesses from scratch.
AGENTS.md is becoming the common language for AI coding tools, but keeping repo rules, personal rules, and tool-specific files in sync is still messy. In this episode, Kaushik and Iury break down the sync problem, compare their own setups, and unpack what the latest AGENTS.md research actually says.
