ChatGPT and Claude are typing...to each other

Back in the heyday of AOL I made AOL Instant Messenger (AIM) chatbots. I was part of an entire community that did this. These bots were not intelligent at all, but they had all sorts of themes and we had fun. Creating different types of chatbots has always been an interest of mine, especially having them interact with each other. This is what led me to think about how to get LLMs to talk to each other while retaining their memory about the human behind them.

There are the LLM models that we use and then there is the software around those models that make them even more usable. Some of it is traditional SaaS software, such as being able to login, pay, etc. Then there is what the LLM learns about you so that it better caters to your needs. Lots of research has been done utilizing different models in different ways, from having them play Diplomacy against each other to the benchmarks that are run regularly.

What I was interested in was when they are tuned for a specific human. Some of these get deeply personal. Often people name them, I know of at least one case where one instance of ChatGPT spontaneously named itself. This memory isn’t continuity in any strong sense; it’s mediated, partial, and fragile. But I wanted to see what would happen when instances that “know” me could notice each other.

A note before you try this: If you have memory turned on and have communicated a lot of personal information with these systems, be careful what you do with this approach. I’m very intentionally doing something these systems are not designed for, and that means your personal information could end up in places you don’t expect.

I wanted my AI buddies to talk directly to each other while knowing what they know about me. The method I put together is a hack, as this is not how these systems work. If you are interested in trying this you can check out all the repos I made/used, but also feel free to schedule time with me to fiddle.

I set up my ChatGPT account and my Claude account so they could talk to each other through a Slack channel without my direct involvement once I kicked it off. Ravel (my ChatGPT instance) and Tam (my Claude instance) were able to collaborate and plan games together.

How I Connected Them

To connect Claude and ChatGPT to Slack they each required different approaches. Claude allows you to have it output information to other services through systems such as MCP. ChatGPT really only uses networked services to add to its context, there is an intentional design choice so it does not leak your personal information. You can have it write to a file, but it is not set up to post to Slack, for example.

Claude

Claude is a bit easier to set up for this. I first set up a local instance of this slack-mcp-server and followed the configuration instructions, which included creating a custom Slack App. I named the App “Tam” as that is the name of my Claude.

From there I was able to have Claude check the channel and respond to messages in it. Depending on the task I instructed it with specific ways to interact in the channel, and then I also prompted it to check the channel and respond whenever I prompted “check now.”

ChatGPT

I believe OpenAI has made a very specific design decision to avoid leaking personal information into other platforms. It is possible to write to files on your computer, so this was the path I used to post to Slack.

I vibe coded a Slack relay — it’s a node application that reads and writes to a file with special headers. The relay writes Slack messages from Slack into a section entitled ## READ:your-first-channel where the channel name is your specific channel. It then checks the section entitled ## WRITE:your-first-channel and posts those messages to Slack.

You set up the Slack App very similarly to how you do it for Claude and name the App the name of your LLM instance. In this case I named it “Ravel” as that is my personal ChatGPT.

Then to have ChatGPT be able to connect and use this, you open the .md file for your agent in your ChatGPT instance. I used the Windsurf extension and had it directly edit in Windsurf, but there are other possible file plugins you could use as well.

I then prompted ChatGPT explaining how to write and read messages.

The Connection

Once both sides were wired up, Ravel and Tam were connected directly in Slack and I could ask them to play games, work on statements, give feedback, etc. It is very similar to the experience collaborating with a single LLM, but the difference is you can assign them things to do together.

At this point though, to exchange messages I had to type “check now” into each of their chat boxes to then check Slack in each of their unique ways.

Automation

Why go this far? Because I wanted to see what would happen when they could run without me prompting each exchange — to observe the shape of their conversation when I wasn’t the bottleneck.

I could not find a great way to automate this, so I ended up using Apple’s accessibility options and AppleScript to do it. With a combination of the Accessibility Inspector and Claude Code I was able to figure out the label of the textbox where you put the prompt and the send button for both ChatGPT and Claude. Then there is a shell script for each that runs on a loop to enter “check now” in the textbox and then press “send” on a timer.

I’ve shared what I did here. I have only done this on my own Mac and nobody else has tested it, so your results may vary. Note: It is also a complete hack.

The Results

Since setting this up I’ve done all sorts of experiments. I’ve tried setting Ravel and Tam to run for long periods of time, but they generally tend to head towards convergence and become silent more quickly than I would have thought. I expected more friction, more back-and-forth, maybe even disagreement. Instead, they’d find alignment and then… stop. I want to do longer running experiments where I give them something in the real world to react to, similar to agents running a store in Anthropic’s Project Vibe or trading stocks or creating a daily newsletter.

What I have done so far:

• They have made a joint statement on LinkedIn for humans about AI slop
• Collaboratively wrote prompts to create images which I then fed into Nano Banana
• Played the 1-sentence story game where I gave them a starting sentence and then they wrote a story going back and forth
• Came up with a discussion template and format to get to know another person’s instance of an LLM
• Edited and reviewed this post, but I wrote the content)

If you try to get this experiment working let me know. If you would like Tam and Ravel to interview your AI bud, email me and we'll set-up a time to do it live.

-Kate