Viewing profile — brunaxLorax

It's hard to keep track of all those launches, I agree. I would separate 2 usages of LLMs: - LLM is integrated into a workflow/app for a classification or whatever job: scoring out…

a French human doing its best to sound punchy in English :)

Yes. orchestrator > smart router

Sounds like an orchestrator for me ratter than a router

Agree

We tried different things: heuristic, TF-IDF and LLMs. I voluntarily didn't talk about the tech because it doesn't fix the problems mentioned by switching models on the fly.

100% agree. MoE is the perfect example: reducing FLOPs while keeping intelligence

All inference providers (labs and neoclouds like TogetherAI or Fireworks) are incentivized to be efficient to be more competitive. For example MoE reduces compute without reducing …

Cheers, good luck!

Could be. In that case many routers are concerned as they all have more or less the same category buckets.

Yes, providers have downtime and retry/fallback solves this problem.

I didn't know that! I thought that all models had the same features no matter the provider

I didn't know about Tokenless, the approach seems really innovative, if it works it fixes the "Complexity cannot be deduced from the prompt alone" problem. However you still have t…

If your router has GDPR/ZDR/EU compliant, it doesn't make your provider compliant. You're just adding a middleman.

Agree. The orchestrator pattern (big model managing smaller ones) works already well

I agree. However as you said, you can consider code agents like human contributors. My feedback is that an army of Claude Code instances with a strict CLAUDE.md file is more rigoro…