Why RAG Finds Documents but Still Misses the Answer
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After building and evaluating dozens of retrieval systems, I stopped thinking retrieval was the real problem. Over the last couple of years I've spent a lot of time building and evaluating RAG systems. Some were quick prototypes. Some powered internal knowledge bases. Some eventually became parts of products. And I kept seeing the same pattern. A user would ask a perfectly reasonable question. The search would work. The LLM would answer confidently. And the answer would still be wrong. Not…
1Key Takeaways
- After building and evaluating dozens of retrieval systems, I stopped thinking retrieval was the real problem.
- Over the last couple of years I've spent a lot of time building and evaluating RAG systems.
- Some powered internal knowledge bases.
- Some eventually became parts of products.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that after building and evaluating dozens of retrieval systems, I stopped thinking retrieval was the real problem.
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