Agent harness

An agent harness is the operational infrastructure wrapping a raw language model to manage tool execution, state, and sandboxed environments, turning static text generation into an autonomous work engine.

While raw language models excel at text generation, they cannot natively execute code, manage persistent state, or call external APIs. The agent harness bridges this gap by serving as the execution layer that orchestrates system prompts, manages tool registries (like the Model Context Protocol), and runs isolated sandboxes. By handling the execution loops and error recovery that models cannot manage alone, a well-engineered harness can dramatically swing benchmark performance (such as LangChain's 13.7-point jump on Terminal-Bench 2.0) without changing the underlying model. This infrastructure layer is what ultimately transforms a static LLM into a reliable, production-ready autonomous agent.

https://langchain-ai.github.io/posts/anatomy-of-an-agent-harness/