You’re Doing RAG Wrong: How to Fix Retrieval-Augmented Generation for Local LLMs

Author(s): DarkBones

Originally published on Towards AI.

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✔️ Want to skip straight to the setup? Jump to the tutorial.

✔️ Need a RAG refresher? Check out my previous article.

RAG Works… Until It Doesn’t

RAG sounds great, until you try implementing it. Then the cracks start to show.

RAG pulls in irrelevant chunks, mashes together unrelated ideas, and confidently misattributes first-person writing, turning useful context into a confusing mess.

I ran into two major issues when building my own RAG system:

🧩 Context Blindness — When retrieved chunks don’t carry enough information to be useful.🤦 First-Person Confusion — When the system doesn’t know who “I” refers to.

I’ll show you exactly how I fixed these problems, so your RAG system actually understands what it retrieves.

By the end, you’ll have a 100% local, 100% free, context-aware RAG pipeline running with your preferred local LLM and interface. We’ll also set up an automated knowledge base, so adding new information is frictionless.

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