How to get multiple AI models to work together (without copy-pasting between tabs)
TL;DR
Most people "use multiple models" by keeping several chat tabs open and copy-pasting context between them, which loses history and invites contradictions. A better approach puts the models in one room with distinct roles and a shared memory, so each one sees what the others said and the project context carries across sessions. Assign roles, address members by name, and let a human make the call.
If you have ever kept ChatGPT, Claude and Gemini open in three tabs and pasted the same context into each one, you already know the problem: the models never actually work together. They work in parallel, blind to each other, and you become the human clipboard holding it all in your head.
Here is a cleaner way to get multiple AI models to collaborate on one piece of work.
1. Put them in one room, not three tabs
The core shift is moving from "several separate chatbots" to "one shared room." When the models share a single thread, each one can see what the others said and respond to it directly, the way a real team does. You stop re-explaining the project every time you switch tools.
2. Give each model a role
A team of identical generalists just repeats itself. Assign roles instead: a Strategist to frame the problem, a Maker to produce the actual artifact, a Critic to red-team it. Putting different models in different roles is where the value shows up, because an independent Critic catches what the Maker is happy to ship.
3. Give the team a shared memory
This is the piece tabs cannot give you. A shared, persistent memory keeps the project state, constraints and past decisions in one place, so the context survives across sessions. Come back next week and the team still knows what you decided and why, no re-pasting required.
4. Keep a human in the chair
Multi-model collaboration is not a vote. The room proposes, builds and critiques; you decide. More perspectives, surfaced cleanly, with one person making the final call, is the difference between a second opinion and noise.
The short version
Stop couriering context between tabs. Put the models in one room, give each a role, give the team a memory, and stay the decision-maker. That is what Bordet is built to do: a boardroom where your AI team works on one project together and remembers it across sessions.
See it for yourself
Open a multi-LLM boardroom and put your AI team to work.