Lately I've been adding a repl service to my docker compose configs so the agent can easily send fragments of code for execution in the project context without incurring the clojure startup costs each time.
replySo cool to watch the AI get into a tight learning loop when it has access to all the internal data structures.
Clearly, you’re not going to do it for just Fibonacci. And yes, you can always rewrite the agent code, quit, and restart to modify the agent. This is just like using an LLM to modify Pi and then restarting, which is done today. But being able to rewrite code in a live, running system is useful for all the reasons that Lispers have done it that way for 50+ years. In some cases, you can’t just serialize your state and reload it easily. Sometimes, for instance, you might not even have access to the whole state because some of it resides on a remote server.
reply> Sometimes, for instance, you might not even have access to the whole state because some of it resides on a remote server.
replyNot sure what you mean. The system I outlined is one where some "state" resides outside the process in a separate server. You don't need to serialize that, you just need to serialize the information to need to reconnect.
And my first point is even more relevant the more complex/distributed/brittle you make the whole thing: The more important it is for some specific process to stay alive no matter what, the less you want to live-slop code into it.
(Edit: Yes I'm aware of the live-patched space probe story. Human live-patching is not the same as letting an LLM try to one-shot the correct patch.)