I'm thinking stuff like this:

https://denverite.com/2026/03/12/ai-recycling-facility-comme...

You could take a model like the one referenced in the article, retool it with Forge for oh I don't know, compost, and use it to flag batches that contain too much paper for instance.

These kinds of applications would work across industries, basically anywhere where you have a documented process and can stand to have automated oversight.

You can fine tune small, very fast and cheap to run specialized models ie. to react to logs, tool use and domain knowledge, possibly removing network llm comms altogether etc.

rag basically gives the llm a bunch of documents to search thru for the answer. What it doesn't do is make the algorithm any better. pre-training and fine-tunning improve the llm abaility to reason about your task.

RAG is dead