How to get multiple AI models to work together (without copy-pasting between tabs)

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.

FAQ

Can I use multiple AI models together?

Yes. The simplest way is to keep several chat tabs open and paste the same context into each, which works for a one-off question but leaves you carrying the history between them. A shared room goes further: the models answer in one conversation, read each other's replies and work from the same project memory.

How do I use multiple AI models at once?

There are three honest options. You can copy and paste between tabs, use an aggregator that sends one prompt to several models and shows the answers side by side, or put the models in one room where they respond to each other. The first two are good for comparing answers; a shared room is for work you will come back to, because the context, the disagreements and the decisions stay in one place.

Is there one platform for multiple AI models?

Yes, several. Some are chat apps that let you switch or compare models in one window. Bordet is an LLM boardroom: Claude, GPT, Gemini, Grok, DeepSeek, Mistral, Llama and others each hold a seat with a role, share one memory of your project and keep an append-only decisions log, and you can swap the model behind a seat without losing anything.

How do developers use several AI models without duplicating work?

Give each model a distinct role and one shared record, so nobody re-explains the project or redoes another model's work. In Bordet a developer can also connect their own coding agent, such as Claude Code, Codex or Cursor, as a member through the MCP connector at /connect, so it can ask the table before a change and log what it decided.

If you want to try it, open a boardroom, give each seat a role, and see how it works.