Agent Harness Engineering: Twenty-Four Practices from an Instrumented Case Study
What this is: twenty-four practices for the half of an agent that is not the model — the loop, the context pipeline, the tool surface, the state it keeps, its trust boundary, its traces, and the doors a human steers it through. Each one is written as the rule, the failure that paid for it, and the form that ports to any implementation. Environment used here: tinycmdr, a single-file, local-first agent harness running as a supervised process on the machine it manages, driving any OpenAI-compatible endpoint — a local llama.cpp server or a cloud API — on macOS, Linux and Windows. Substitute your own stack; the practices are implementation-agnostic by construction, and the measurements are one harness’s answers rather than targets. ...