Harness Engineering Course

Why This Matters Most real AI system failures are misdiagnosed. A team blames the prompt when the retrieved context is stale. They blame the model when the tool surface is too broad, the verifier is missing, or the loop has no clean stopping condition. They ask for a larger model when the real problem is that the surrounding system is making the model solve the wrong task. That diagnosis problem is why the trilogy matters. Prompt engineering was the obvious first discipline because early LLM work happened one inference at a time: write a better instruction, get a better answer. Production agent systems retrieve, compress, route, call tools, inspect state, ask for approval, retry, recover, and terminate.

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