I moved all my commit and pr content generation to batch mode a while ago. Moving ci troubleshooting and bug reports to it shortly too.
You’ve just got to pick the right workloads and have the workflow setup so humans aren’t sweating while it works. Even then it’s still not that slow anyway.
@thsottiaux@thsottiaux It would be REALLY great if widgets like multi-choice questions could be surfaced via the app server for plugins and other automations to use.
@LaFrogman@YatimaOfKonishi@macjshiggins I played with an idea like this before and came up with the idea of making three or more light sources which when they converge turn into enough energy to nuke him.
Orchestration of multiple tiers of agents. Plus it still has a bunch of weird stalls when you’re running more than 5 or 6 things at once.
Also… losing chats/sessions when you move between providers/proxies is terrible. If I’ve worked in a directory with codex ever it should show me ALL my previous chats/sessions unless I’ve archived them.
@thsottiaux any chance we could get a “Fly My Pretties” mode for codex that makes codex hard remember that it is the orchestrator and it should be using subagents that use the right model and thinking level for each task?
It still regularly forgets that it’s meant to be delegating work and starts doing everything itself.
I want a “Fly My Pretties” mode that makes codex hard remember that it is the orchestrator and it should be using subagents that use the right model and thinking level for each task.
It still regularly forgets that it’s meant to be delegating work and starts doing everything itself.
We finally know why LLMs hallucinate. It's not the model. It's the geometry.
@OpenAI text-embedding-3-large: 91/3072 dimensions do real work.
@GeminiApp gemini-embedding-001: 80/3072 dimensions do real work.
~97% of your vector database is mathematically empty. Your RAG system is retrieving from noise.
@ashwingop and I present "The Geometry of Consolidation" - a proof that RAG compression has a hard floor no algorithm can beat, set by a single spectral number your embedding model cannot escape.
Every hallucination your RAG pipeline produces? This is why.
Paper + results: https://t.co/zut8pdoPbH