In AI development, a harness is a framework or scaffolding that wraps around an agent to manage how it runs, what it can access, and how its behavior is evaluated. Think of it as the controlled environment the agent operates inside — similar to how a test harness in software engineering runs code under structured conditions.

A harness typically handles things like giving the agent access to tools (web search, code execution, file systems), managing the loop of actions the agent takes, logging what it does, and enforcing limits on what it's allowed to do. Without a harness, an agent would just be a model — smart, but with no structured way to act in the world or be safely evaluated.

Harnesses are especially important in agent benchmarks and safety research, where researchers need to measure what an agent can actually accomplish under consistent, reproducible conditions.