How to Make ChatGPT, Claude, and Gemini Work Together

Different AIs are great at different things: Claude writes clean code, Gemini spots bugs, and ChatGPT brainstorms like a pro. But when your team jumps between them, you hit the same wall: none of them remember your context.

Every time you switch tools, you're re-explaining your company, your product, your progress — again and again. That's hours lost, and worse — fragmented knowledge.

The Real Problem

Teams don't need five separate AI agents. They need one shared brain — a master context that all AIs can draw from. Something that keeps your docs, PDFs, and chat exports in sync, so you never have to "re-feed" context manually. Think about it: you wouldn't hire five brilliant consultants and then make each one start from scratch every time they work on your project. Yet that's exactly what happens when you switch between AI tools.

What This Looks Like in Practice

Monday: You brief ChatGPT on your product roadmap and get great brainstorming ideas for new features. Tuesday: You want Claude to review the code implementation, but you have to re-explain the entire product context again. Wednesday: Gemini finds a critical bug, but it doesn't understand why certain design decisions were made because it has no context from Monday's brainstorming.

Each AI gives you great individual results, but they can't build on each other's work. You lose the compound intelligence that comes from connected thinking.

How We Solved This

Our team has been testing a solution for the past week, and it's been a game-changer. We're saving at least 30 minutes per day per team member by not having to re-explain context every time we switch AI tools. The system works like this:

Centralized Knowledge: All your conversations, documents, and decisions live in one place. No more scattered context across different platforms. Universal Access: Any AI tool can tap into your shared brain. Claude gets the same context as ChatGPT, which gets the same context as Gemini. Continuous Learning: Every new conversation adds to your knowledge base. Your context gets richer over time, not reset with each new chat.

The Results

Imagine asking ChatGPT to brainstorm, then seamlessly having Claude implement with full context of your brainstorming session. Or having Gemini debug code while understanding the business requirements that shaped those technical decisions. That's the power of connected AI workflows — each tool builds on the others' work instead of starting from zero.

Your team's knowledge compounds instead of fragmenting. New team members onboard faster because the context is preserved and accessible. And your AI conversations become exponentially more valuable because they build on everything that came before.

Want to Try This Approach?

If you're interested in testing this kind of connected AI workflow, we'd love to hear from you. The tool we've been using (Feed Bob) is currently in beta testing with select teams.