Like some others, I also built this myself. Overly simply, with tmux, a memory tree, and handoff files and an orchestrator. And yet for how simple it was, it was so effective at minimizing the amount of duplicate context. It's like having shared specialist subagents who source and derive important shared knowledge from separate threads. It's useful because some skills just take too much of a token penalty to invoke and a single shared persistent session just lets that issue melt away. One agent pays the cost of that large skill once, and you don't have to keep paying for it in input tokens for the rest of that conversation.
With clean I mean the opposite of how I currently do it, which is by asking the model to compact the whole thread into a prompt which will act as context for next model.
My way of prompting this varies and every time I receive the blob of output, I can’t fell how well it managed to capture the necessary details. This way feels lika a dirty way to transfer knowledge from one conversation to another.
I was reading about the HF hack and one of the first thing the GPT swarm did was build a messaging system for themselves. This reminded me of that. (Also of how weirded out I was by Moltbook when it came out. Time flies!)
Unrelated: when my Claude/Codex finishes cooking (or needs my attention), it pings a local HTTP endpoint that plays a frog sound on my laptop. I found this massively boosts quality of life.
I have built this with Claude as a script, but it can also message other models and get responses from them, and throughout my fleet of Linux machines via Tailscale. It's been mostly very useful, although occasionally you have to step in and interrupt if they start going the wrong way.
Tried to have Claude demo this to me in the standalone Mac OS app. It didn't even know what I was talking about. Then I realized maybe it's only in CC. So I go over to CC and ask it to demo this functionality and it wants to demo via subagents. I correct it that I want separate chats to message each other. It tells me I need to open another Claude session in another terminal of course and just leave it sitting there. So I do that and it has me copy a message to the new conversation, it needed to like name itself or something internally.
It worked, but clunky. Way clunky compared to codex.
Like some others, I also built this myself. Overly simply, with tmux, a memory tree, and handoff files and an orchestrator. And yet for how simple it was, it was so effective at minimizing the amount of duplicate context. It's like having shared specialist subagents who source and derive important shared knowledge from separate threads. It's useful because some skills just take too much of a token penalty to invoke and a single shared persistent session just lets that issue melt away. One agent pays the cost of that large skill once, and you don't have to keep paying for it in input tokens for the rest of that conversation.
I wish there was a clean way to compact the conversation into a prompt with all necessary context for a new fresh conversation.
There is, but your wish of "clean" is ambiguous.
With clean I mean the opposite of how I currently do it, which is by asking the model to compact the whole thread into a prompt which will act as context for next model.
My way of prompting this varies and every time I receive the blob of output, I can’t fell how well it managed to capture the necessary details. This way feels lika a dirty way to transfer knowledge from one conversation to another.
You said there is? What’s the options?
Here's a view for "clean:"
1. Every chat should have a context used/remaining measurement so you know when you have to ditch the current chat for a fresh one.
2. Every chat should analyze and categorizes each element of context by how useful it is towards the overarching goal of the chat.
3. Every chat has a handoff button with a "usefulness" slider (say 1-5) that shows the total size of the context based on its setting.
4. The handoff automatically creates a new chat with the desired amount of context and a prompt to get it back to where you were.
That said, I am newb and so there is some reason why these non-deterministic LLMs can't do this :-/
I was reading about the HF hack and one of the first thing the GPT swarm did was build a messaging system for themselves. This reminded me of that. (Also of how weirded out I was by Moltbook when it came out. Time flies!)
Unrelated: when my Claude/Codex finishes cooking (or needs my attention), it pings a local HTTP endpoint that plays a frog sound on my laptop. I found this massively boosts quality of life.
How do you know when they’re done (or need your attention)? Is that a standard “api”/hook? I want that!
I have built this with Claude as a script, but it can also message other models and get responses from them, and throughout my fleet of Linux machines via Tailscale. It's been mostly very useful, although occasionally you have to step in and interrupt if they start going the wrong way.
Tried to have Claude demo this to me in the standalone Mac OS app. It didn't even know what I was talking about. Then I realized maybe it's only in CC. So I go over to CC and ask it to demo this functionality and it wants to demo via subagents. I correct it that I want separate chats to message each other. It tells me I need to open another Claude session in another terminal of course and just leave it sitting there. So I do that and it has me copy a message to the new conversation, it needed to like name itself or something internally.
It worked, but clunky. Way clunky compared to codex.
I hacked this together with a small local irc server
I've used this feature and saw some weird messages:
> hold swarm, I prepare safe exfil
i miss when opencode let you interact with your subagents. that was so so so much better.
I broadly miss this feature to allow user agency, in letting users work with the various agents at they please, and to send data around.
Claude Code does allow this. You can talk to the subagents directly and watch what they are doing.