Your AI Agent Doesn’t Need a Better Model The problem might not be the model. It might be the harness. A harness is the system around the model that helps it actually complete useful work. Think of it as the layer that provides: Context — what information the agent can access Tools — what actions it can take Checks — how it verifies its work Stop rules — when it should stop or hand control back And there’s an important difference between three concepts: Prompt engineering: What you ask the model. Context engineering: What information the model sees. Harness engineering: How the entire workflow runs, checks itself, recovers, and improves. A reliable AI agent should be able to: Read the right files Make an edit Run checks Read the failures Fix the issue Check again Hand control back when it can’t safely continue The goal isn’t to make the agent run forever. The goal is to make “done” verifiable. If your AI agent keeps breaking things, stop asking only, “Which model should I us...