Brains vs Hands: How to Run AI Agents Safely in Production — Viren Baraiya
Oct 9, 2026AI Engineer
Summary
This post introduces the concept of running AI agents in production by framing their harnesses as applications, akin to microservices, rather than simple components. It advocates for a strict separation between the LLM's planning ('brain') and the deterministic, durable execution engine ('hands'). The Orkes Conductor is presented as a solution for this, enabling agents to be scheduled, event-driven, and long-running. Key features highlighted include human approval gates, idempotent steps, recorded side effects, and the compilation of agent plans into durable workflows, effectively treating agent harnesses as late-bound sagas.
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
- Stop Prompting — Greg Pstrucha, Sentry
- We Mapped 115 Microservices for Our Coding Agents — Kamalakannan Nandagopal, Postman