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Concept Stack 08 Stack 06
Agent harness
Draft · pending editorial review Verified Oct 16, 2026 Review by Apr 14, 2027 4 sources
Short answer
The harness is everything around a model that makes it usable: tools, file access, memory, permissions, the interface and the loop that runs it. Practitioners including Ethan Mollick and Simon Willison argue the harness explains much of the gap between benchmark scores and real-world results.
What it is
If the model is the engine, the harness is the rest of the car. It includes the system prompt, tools and connectors (MCP), memory, file access, the sandbox the model runs in and the review loop.
How it works
The harness decides what the model sees, what it can do and how its work is checked. Two products built on the same model can behave very differently because their harnesses differ. Ethan Mollick made this point about a strong model held back by its interface. Simon Willison reached the same conclusion with local models: results depended on finding the right model-and-harness combination.
Benefits
- Better buying decisions. Judge AI tools on what they can do with your files and systems, not on model benchmarks alone.
- Vendor flexibility. Satya Nadella has described keeping the harness, context, memory and actions separate from any one model family, so a company can swap models without rebuilding.
- Faster fixes. Christopher Penn argues that most bad output in agent setups is a harness problem (missing examples, data or guardrails), not a model problem.
Limits and risks
- Seller bias. Several voices on this topic sell harnesses. Weigh their claims accordingly.
- Not yet measured. These are informed practitioner views. We found no controlled comparison.
Best-fit stacks
Ops & admin automation
Hand repeat admin (receipts, logs, notices, handoffs) to workflows your agent can trigger.
Agent compatibility
| Tool in this entry | How agents connect |
|---|---|
| Claude | Agent platform API/CLIBulk import |
| Cursor | Agent platform API/CLI |
| ChatGPT | Agent platform API/CLIBulk import |
Levels come from each tool's recorded, sourced compatibility. How the levels work.
Related entries
AI agent · ConceptSystem prompt · ConceptWhich AI model should I use for a business task? · QuestionAgent platforms · ServiceAI coding agents and editors · ServiceClaude (Anthropic) · ModelHow do I avoid getting locked into one AI vendor? · QuestionMuse models (Meta) · ModelShip code faster with AI · Need
Sources
- Post on harness and UX limiting model capability · Ethan Mollick, 2026-03-03Practitioner view accessed Oct 16, 2026
- Post on finding the right harness and model combination · Simon Willison, 2026-07-31Practitioner view accessed Oct 16, 2026
- Post on separating harness, context, memory and actions from any one model · Satya Nadella, 2026-07-30Practitioner view accessed Oct 16, 2026
- You Ask, I Answer: Evaluating LLMs the Wrong Way? · Christopher Penn, 2026-08-13Practitioner view accessed Oct 16, 2026
Practitioner views are restated in our words and labeled as views, not measured results. Product facts come from official sources dated above.
To verify before publishing
- A measured study of harness vs model effect (none found in Scout)
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