this post was submitted on 02 Mar 2026
52 points (98.1% liked)
Programming
25948 readers
100 users here now
Welcome to the main community in programming.dev! Feel free to post anything relating to programming here!
Cross posting is strongly encouraged in the instance. If you feel your post or another person's post makes sense in another community cross post into it.
Hope you enjoy the instance!
Rules
Rules
- Follow the programming.dev instance rules
- Keep content related to programming in some way
- If you're posting long videos try to add in some form of tldr for those who don't want to watch videos
Wormhole
Follow the wormhole through a path of communities !webdev@programming.dev
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
As further evidence of this, RAG was supposed to enable this. Instead, we've found that RAG was nothing more than an overused buzz-term that has limited applications, and often results in hallucination anyway.
Rag was never supposed to be about learning over time. It was supposed to provide better context at inference. It could never scale to handle new learning beyond focused concepts.
The way it was presented with regards to search engines was that it was supposed to pull data that was more up-to-date than when the model was trained. It does do that, actually, and provides better results too, on average anyway.
But that's just one domain, and "better" doesn't mean "good" or "accurate". In most domains, at least where I work, we've found that RAG overcomplicates things for little benefit, unfortunately.