Beyond the Model Call: The Essential Guide to Harness Engineering for AI Agents
In the rush to build autonomous AI systems, developers often start with a fundamental misconception: assuming a capable language model is by itself a working agent . A raw language model is simply a statistical inference engine. Abstractly, its entire existence is captured by: y ∼ p θ (· | c) Notice what is missing from the above expression: nothing here automatically opens a browser, runs a shell command, retries a timed-out API, preserves state across hours of work, or verifies whether a requested task actually succeeded. p θ (· | c) represents the models complete output probability distribution across possible token/sequences given prompt context c. To turn a probabilistic model into a reliable production agent, you need an external control process. The surrounding infrastructure hosting external control process is known as the Agent Harness . SYSTEM ARCHITECTURE OVERVIEW +-------------------------------------------------------------------...
