This is the final part of our five-part series on agentic harnesses. We've defined what a harness is and walked through its four parts: the agent loop and tools, context management, and verification and control. This post is about the practice: how you build one, grow it, and know when to take parts of it away.
Agent = Model + Harness
The cleanest way to hold the whole series in your head is a formula Mitchell Hashimoto put forward in 2026:
Agent = Model + Harness.
The model is the raw intelligence you rent from a provider. The harness is everything you build around it: guides that direct the agent, sensors that validate its behaviour, the data pipelines that feed it context. You mostly can't change the model. The harness is entirely yours, and that's where your leverage and competitive edge live.