Building a Harness: From Prototype to Production

TL;DR An agent doesn’t truly work because of the model, but because of the harness controlling it. Moving from demo to production requires handling errors, state, memory, and observability. A well-designed harness reduces model unpredictability and shifts complexity into code, making the system reliable and usable in real-world scenarios. In article Harness Engineering: The Most Important Part of AI Agents we saw a fundamental point: the problem with agents isn't (only) the model, but the system