This is still retrieval and RAG, just not vector search and indexing. it’s incredibly important to be clear about terms - and this article does not meet the mark.
Traditional RAG for code uses vector embeddings and similarity search. We use filesystem traversal and AST parsing - following imports, tracing dependencies, reading files in logical order. It's retrieval guided by code structure rather than semantic similarity.
I highly recommend checking out what the Claude Code team discovered (48:00 https://youtu.be/zDmW5hJPsvQ?si=wdGyiBGqmo4YHjrn&t=2880). They initially experimented with RAG using embeddings but found that giving the agent filesystem tools to explore code naturally delivered significantly better results.
From our experience, vector similarity often retrieves fragments that mention the right keywords but miss the actual implementation logic. Following code structure retrieves the files a developer would actually need to understand the problem.
So yes -- I should have been clearer about the terminology. It's not "no retrieval" -- it's structured retrieval vs similarity-based retrieval. And with today's frontier models having massive context windows and sophisticated reasoning capabilities, they're perfectly designed to build understanding by exploring code the way developers do, rather than needing pre-digested embeddings.
Indeed, industry at large sees RAG as equivalent to "vector indexes and cosine similarity w.r.t. input query", and the rest of the article explains thoroughly why that's not the right approach.
Yep, and this is getting really old. Information retrieval is not a new problem domain. Somehow, when retrieved info is fed into an LLM, all nuance is lost and we end up with endless pronouncements about whether retrieval is/is not "dead".
It would be wondeful if some of the tools the projects uses are exposed to build on. Like the tools related to AST, finding definitions, and many more
For instance, everyone seems to believe that em dashes are something only an AI would use -- but I've been using them in my writing for a long time.
Yes by technicality RAG could mean any retrieval, but in practice when people use the term it’s almost always referring to some sort of vector embedding and similarity searching.
Is it? None of these terms even existed a couple of years ago, and their meaning is changing day by day.