Will bigger context windows make RAG unnecessary?

Large language models can now read much more information at once, which raises a practical question: will retrieval-augmented generation still be needed? The main issue is whether putting all available material into the context window is cheap and fast enough for real products. Retrieval-augmented generation can reduce cost and delay by adding only the most useful information to the model’s input.

It can also help with fresh information, more precise context, and rules about who is allowed to access which data. Over the next few years, production AI systems may need to balance “put everything in the context window” against “search first, then send only what matters.”