Rent the model, own the harness: how to build a model-agnostic AI agent

Description and use

<p>Developers have Claude Code or Codex. Office workers have Claude Cowork or ChatGPT Work. Each of these is a harness: the scaffolding around an AI model that lets it do real work, with tools, context and rules. The person installing solar panels on a roof has nothing built for their work.</p> <p>At Werk we built one for teams on the move, and our first decision was to keep it separate from the model: the model understands and proposes, and the harness decides what it reads, what it touches and what gets recorded. Four practices make that possible: talk to models through an interface of your

Problem

<p>Developers have Claude Code or Codex. Office workers have Claude Cowork or ChatGPT Work. Each of these is a harness: the scaffolding around an AI model that lets it do real work, with tools, context and rules. The person installing solar panels on a roof has nothing built for their work.</p> <p>At Werk we built one for teams on the move, and our first decision was to keep it separate from the model: the model understands and proposes, and the harness decides what it reads, what it touches and what gets recorded. Four practices make that possible: talk to models through an interface of your

Outcome

<p>Developers have Claude Code or Codex. Office workers have Claude Cowork or ChatGPT Work. Each of these is a harness: the scaffolding around an AI model that lets it do real work, with tools, context and rules. The person installing solar panels on a roof has nothing built for their work.</p> <p>At Werk we built one for teams on the move, and our first decision was to keep it separate from the model: the model understands and proposes, and the harness decides what it reads, what it touches and what gets recorded. Four practices make that possible: talk to models through an interface of your

Evidence

Rent the model, own the harness: how to build a model-agnostic AI agent

Source