Tagged: RAG

5 articles on rag.

RAG Isn't Dead. You're Just Using It Wrong.

RAG Isn't Dead. You're Just Using It Wrong.

The 'RAG is dead' narrative is wrong — but it's wrong in an interesting way. After building RAG systems in healthcare production, here's what actually kills LLM context quality and what to do about it.

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Beyond Chunks: Why Faceted Context Is the Future of RAG

Beyond Chunks: Why Faceted Context Is the Future of RAG

Chunk-based RAG returns results. Faceted context gives agents peripheral vision — an understanding of the information landscape that lets them navigate rather than just consume. Here is what that looks like in a domain where getting it wrong actually matters.

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Context Rot: The Silent Performance Killer in Your LLM Application

Context Rot: The Silent Performance Killer in Your LLM Application

Your LLM system works great in demos and degrades in production. The culprit is almost never the model. It's what you're feeding it. Here's how to diagnose and fix context rot before it kills your product.

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Building a GenAI Platform That Doesn't Collapse Under Its Own Weight

Building a GenAI Platform That Doesn't Collapse Under Its Own Weight

Most GenAI platforms fail not because the models are bad, but because teams build everything at once. A practitioner's guide to layered GenAI architecture — from the minimal production-ready core to healthcare-grade guardrails and beyond.

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Why I Stopped Using RAG for Coding Agents (And What I Do Instead)

Why I Stopped Using RAG for Coding Agents (And What I Do Instead)

The instinct when building a coding agent is "I need RAG to handle large codebases." The better instinct is giving the agent tools to explore code the way a senior engineer would — reading files, following imports, tracing execution.

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