Engineering-Principles

AI harness engineering is the practice of building the orchestration layer around an AI model — the tools, context, control flow, and verification that turn a raw LLM into a useful agent. The principles: 1. Context is the budget Every token in the window competes. Curate aggressively: load on demand, summarize aging history, evict what is stale. The harness’s job is to put the right context in front of the model at the right time, not all the context. ...