What Is an AI Harness?

An AI harness is what connects an AI model to everything it needs to do a job. Technically, it's the software around the model that decides what to send it and which tools it can use. For a business, the harness that matters loads your company context, pulls the right documents from your knowledge base and fetches the right skill, every time, so your AI starts with the full picture.

Microsoft's Copilot Studio documentation gives a clear definition. The harness is a runtime that sits between what you build and the model you choose. It decides when to call the model, what to send it, how to read what comes back and which tools to call (Microsoft: Harnesses in Copilot Studio).

Anthropic's engineering team has written about harnesses for agents that work across many sessions. A large part of their approach is the start: each new session begins by reading a progress file, the recent history and a list of what's left, so the agent gets its bearings before it does anything (Anthropic: Effective harnesses for long-running agents).

Both point to the same idea: the model supplies the reasoning, but what it achieves depends on what it's given.

In new-starter terms, the model is a capable new hire. The harness is the manager who, before every job, hands them the induction pack, the right manuals and the job card. Without that, they start each job with whatever they happen to remember.

It helps to think of a harness in two layers. This split is our way of explaining it, not an industry standard.

The AI tools already provide the technical layer. The business layer is usually missing, so each person's AI starts from a different place: one colleague pastes in the style guide, another works from an old price list.

• Your company context. Who you are, the words you use and how you lay out work, loaded before anything else. Without it, the AI writes generic work in the wrong terms.
• Your knowledge base. The SOPs, templates, guidelines and scripts the job needs, found where they live. Without it, the AI makes up the detail.
• The right skill. The method for the job in front of it, in its current published version. Without it, the AI improvises.
• The right space. Which team's home and rules apply, so finance work draws on finance's folders and sales work on sales'.
• Every time, in every AI. The same pieces, brought together the same way, whichever tool someone opens. Without this, results depend on who asked and where.

A harness isn't a set of checks or a sign-off step. Those belong inside individual skills, written into the skill's own instructions, such as "every price matches the rate card" or "stop for approval before anything is sent". The harness makes sure your AI has the skill that contains them.

Ridgeline Advisory, a fictional consultancy, prepares a proposal for Harbour Foods, a fictional client.

Without a harness, three consultants ask three AI tools and get three different proposals. One AI doesn't know Ridgeline prices in fixed-fee phases, so it quotes hourly rates. Another uses a template pasted in last year. The third finds an old rate card, because nothing tells it which file is current.

With a harness, the setup happens before the work starts. The AI loads Ridgeline's company context: its name, its fixed-fee phases, its spelling and how its proposals are laid out. It picks the sales space, whose home is the sales folder in SharePoint, and goes to the current template, the rate card and the Harbour Foods meeting notes there, opening them with its own access. It fetches the published proposal skill, the same version every consultant gets. Then it does the work. The skill's own checks, such as matching every price to the rate card, come with it because they're part of the skill.

• Pick one job your team repeats, such as a proposal or a client update.
• Write down the company context the job needs: your name, offer, terms, formats and tone.
• List the documents it needs from your knowledge base, where each one lives and which version is current.
• Name the skill for the job, or write one using How to Create an AI Skill.
• Check that each AI tool your team uses can open those documents with its own access.
• Note where each piece lives today. Anything pasted in by hand or kept in one person's chat history is a gap.
• Run the three tests below.

• A normal request. Ask for the proposal with no extra instructions. The AI should use your name, terms and layout, open the current template and rate card, and follow the skill without being told to. Ask it which documents and which skill it used.
• Incomplete input. Move the rate card or remove the AI's access to it. The AI should say it can't reach the document, not price from memory.
• An unrelated request. Ask a quick general question, such as what a contract term means. The AI should still know who you are, but the proposal skill shouldn't take over.

Then make the same request in a second AI tool. The start should be the same.

A skill tells your AI what to do. Your knowledge base shows it how, in detail. Your company context tells it who it's for. The Contexta harness brings them together, in every AI.

The Contexta harness is what connects your AI to everything it needs. It reaches each AI tool through one MCP connection, and at the start of every session it:

• Loads your company context: your organisation's rules, covering terminology, naming and formats, with your team's rules on top.
• Picks the right space: company, team and personal spaces route each piece of work to its own SharePoint or Google Drive folders, with their own rules and audience.
• Pulls the right documents: built-in knowledge base skills tell your AI where to look and how to find what the job needs. Contexta doesn't store or index your documents; your AI reads them where they are, with its own access.
• Fetches the right skill: the published version, the same in Claude, ChatGPT and Cursor, the tools tested with Contexta.

Best practice is built into how it does this. Every change to a skill or rule is kept in version history, so you can compare and restore. See How It Works for how it fits together.