RAG could largely be replaced with tool use to a search engine. You could keep some of the approach around indexing/embeddings/semantic search, but it just becomes another tool call to a separate system.
How would you feel about becoming an expert in something that is so in flux and might disappear? That might help give you your answer.
That said, there's a lot of comparatively low hanging fruit in LLM adjacent areas atm.
> How would you feel about becoming an expert in something that is so in flux and might disappear?
Isn't that true for almost every subject within computers though, except more generalized concepts like design/architecture, problem solving and more abstract skills? Say you learn whatever popular "Compile-to-JS" language (probably TypeScript today) or Kubernetes, there is always a risk it'll fade in popularity until not many people use it.
I'm not saying it's a problem, as said by someone who favors a language people constantly claim is "dying" or "disappearing" (Clojure), but more that this isn't exclusive to the LLM/ML space, it just seems to happen slightly faster in that ecosystem.
So instead, embrace change, go with what feels right and learn whatever seems interesting to you, some things stick around, others don't (like Coffeescript), hopefully you'll learn something even if it doesn't stick around.
RAG could largely be replaced with tool use to a search engine. You could keep some of the approach around indexing/embeddings/semantic search, but it just becomes another tool call to a separate system.
How would you feel about becoming an expert in something that is so in flux and might disappear? That might help give you your answer.
That said, there's a lot of comparatively low hanging fruit in LLM adjacent areas atm.