Harness engineering for coding agent users
AI Summary
Agent = Model + Harness. Böckeler's framework separates guides (feedforward controls that prevent problems) from sensors (feedback controls that catch them) as the path to trusting agent-generated code.
Original excerpt
Böckeler — who leads Thoughtworks' AI-assisted delivery practice — gives the harness its own engineering discipline. Her equation: Agent = Model + Harness. You don't control the model, so all your leverage is in the harness, and she splits that leverage into two control types.
Guides are feedforward: linting rules, conventions files, scoped permissions, and prompts that prevent classes of failure before the agent acts. Sensors are feedback: tests, typechecks, review gates, and runtime checks that catch what the guides missed. Trust in agent output is built by layering both, not by hoping the model got better.
Published on Martin Fowler's site — the traditional home of software-practice essays…
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Agent = Model + Harness. Böckeler's framework separates guides (feedforward controls that prevent problems) from sensors (feedback controls that catch them) as the path to trusting agent-generated code.
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"Harness engineering for coding agent users" was written by Birgitta Böckeler. It is curated in the Agentic Engineering vault on Burn 451, which covers engineering with ai coding agents.
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Content attributed to the original author (Birgitta Böckeler). Burn 451 curates publicly available writing as a reading index. For removal requests, contact @hawking520.