An AI agent harness is the operational layer around a model. It determines what an agent knows, what it can do, where it runs, and how you evaluate its results.
Layer
Purpose
Context
Scope repositories, tickets, decisions, and domain rules for each run
Tools
Expose typed actions with explicit permissions
Authority guardrails
Reserve sensitive or destructive decisions for people
Runtime
Provide isolated, reproducible execution and an audit trail
Evaluations
Measure task outcome, boundary adherence, cost, and latency
Keep context, tools, policies, and evaluations outside the model. This lets you compare or replace model providers without rebuilding the operational controls around an agent.
