Guide
By AnyCap Team
What is an
agent harness?
An agent harness is the execution layer around an AI model. It gives the agent access to files, terminals, tools, browser actions, permissions, and runtime policies. The model may decide what to do, but the harness defines what it can actually do in the real world.
Agent model vs agent harness
| Layer | Role | Example |
|---|---|---|
| Model | Reasoning, planning, language generation | The LLM decides whether to read a file, ask a question, or call a capability |
| Harness | Execution surface and safety boundaries | Files, shell, browser, permissions, tool contracts, and workflow policies |
| Capability runtime | Curated capability layer the harness can expose | AnyCap provides image generation, video generation, image read, and video analysis through one interface |
Where AnyCap fits
AnyCap is not the model itself and not the entire harness. It sits inside the harness as a capability runtime. That means it gives the harness a consistent way to expose multimodal actions to the agent.
This is an important distinction. The harness provides the execution environment. AnyCap provides the multimodal capability layer the harness can surface to the agent with one CLI, one auth flow, and one interface.