Many coding agents fail because they improvise internal planning loops, leading to unchecked code or runaway sessions. This article details how externalizing a structured Plan-Do-Check-Act (PDCA) engineering loop into a disk-based workflow acts as a leverage multiplier. By forcing agents through an explicit, step-by-step verification process, developers can reliably guide agents to finish what they start with minimal human intervention.

In this episode, we're joined by Josh Collier, FinOps Lead at Superhuman (formerly Grammarly), to explore what it really costs to run AI at scale and why the rules of the game changed faster than anyone expected.

In this episode, we're joined by David Soria Parra, Engineering Lead at Anthropic and one of the core maintainers of the Model Context Protocol (MCP), to explore the biggest evolution of the protocol since its launch and why MCP is becoming the foundation for the next generation of AI agents.