Audit initiation
AI Models & Assistants / Knowledge library
Agent Harness
Wraps a model with instructions, tools, state, policies, and an execution loop
Why learn Agent Harness?
It turns a stateless model call into a controllable, observable system that can complete multi-step work.
The problem it solves
It coordinates model reasoning with real tools, persistent state, safety checks, and termination rules.
Where it came from
An agent harness is the application layer around a model that assembles context, exposes capabilities, executes actions, records results, and decides when a run pauses or ends. The model proposes behavior; the harness owns the operational boundary.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Define Agent Harness and identify its place in an agent architecture.
- Choose a task where Agent Harness improves an agent system.
- Diagnose one failure caused by misusing Agent Harness.
- Interpret a trace or state transition involving Agent Harness.
- Explain one operational tradeoff of Agent Harness.
Documentation and sources
- OpenAI Agents SDK documentation (openai.github.io)
Connect the ideas
Explore next
Agent RuntimeTool-Calling AgentsAgent StateAgent GuardrailsPrompt Chaining WorkflowSandboxed Agent Execution
Real World Example
Automated Compliance Audit Orchestration
Financial institutions managing complex regulatory reporting requirements.
The business problem
Manual compliance audits are prone to human error, slow to execute, and struggle to integrate disparate data sources across legacy systems.
How this topic solves it
The Agent Harness wraps a specialized compliance agent with specific instructions, regulatory tools, and a persistent execution loop to automate data retrieval and validation.
- Define the Agent with system instructions tailored to specific financial regulatory frameworks.
- Equip the Agent with function tools that interface with internal databases and external APIs.
- Implement guardrails to validate that all extracted data meets strict schema requirements before reporting.
- Configure a persistent session to maintain context across multi-step audit workflows.
- Deploy the Runner to manage the execution loop until the compliance report is finalized.
The flow shows how the Agent Harness manages the lifecycle of a compliance task.
Wraps model, tools, and state
Data retrieval and validation
Input/Output validation
Output generation
- User Request → triggers → Agent Harness
- Agent Harness → invokes → Function Tools
- Function Tools → validates → Guardrails
- Guardrails → loop continues → Agent Harness
- Agent Harness → completes → Final Report
Expected business outcome
Increased consistency in audit reporting and significant reduction in manual processing time for compliance teams.
Limitations and checks
The harness relies on the model's ability to interpret instructions correctly; verify this by monitoring the built-in tracing logs for unexpected tool usage patterns.