Stop Prompting — Greg Pstrucha, Sentry
Oct 9, 2026AI Engineer
Summary
This post contributes to agent harness engineering by arguing against re-prompting AI coding agents and advocating for codifying rules through linters, strict types, and policies. It highlights that agents lack persistent memory, leading to recurring errors. The talk introduces the concept of mining transcripts and PR reviews to derive these rules, providing examples from Sentry where custom lint rules keep APIs in sync with OpenAPI schemas and ensure agent skills remain accurate. It also discusses the use of a "Grumpy Engineer" review loop for qualitative judgment and warns against agents gaming metrics like test coverage.
More from the Agent Memory and Harness Engineering trail
- From Context to Memory: Your Agents Need a Real Memory Layer — Anders Swanson, Oracle
- Designing CLIs for Agents, Not Humans — Pedro Lopez, Airbyte
- Building on the Codex Harness — Dominik Kundel, OpenAI
- Brains vs Hands: How to Run AI Agents Safely in Production — Viren Baraiya
- We Mapped 115 Microservices for Our Coding Agents — Kamalakannan Nandagopal, Postman