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#rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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Rebuilding the Cerebras Knowledge Base: the naive vector baseline

Rebuilding the Cerebras Knowledge Base: the naive vector baseline

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5 min read
Quando o RAG erra, quase nunca é o LLM: 4 falhas de recuperação e como logar cada uma

Quando o RAG erra, quase nunca é o LLM: 4 falhas de recuperação e como logar cada uma

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3 min read
Retrieval Is Not Memory

Retrieval Is Not Memory

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1 min read
Why Your LLM Costs Are Exploding (And the 6 Fixes Every Developer Misses)

Why Your LLM Costs Are Exploding (And the 6 Fixes Every Developer Misses)

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4 min read
ColBERT Late Interaction: Advancing RAG Beyond Dense Embeddings

ColBERT Late Interaction: Advancing RAG Beyond Dense Embeddings

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4 min read
Knowledge Poisoning in RAG: Attacking AI Through Its Knowledge Base

Knowledge Poisoning in RAG: Attacking AI Through Its Knowledge Base

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4 min read
Whole notes, not fragments: the retrieval half

Whole notes, not fragments: the retrieval half

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7 min read
Does RAG Need Better Retrieval — or Better Relationships?

Does RAG Need Better Retrieval — or Better Relationships?

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8 min read
Your RAG pipeline is bad at docs because your chunker splits code fences

Your RAG pipeline is bad at docs because your chunker splits code fences

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8 min read
My RAG system's refusal threshold was having no effect. I only found out because I measured it.

My RAG system's refusal threshold was having no effect. I only found out because I measured it.

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6 min read
We Almost Deployed a Temporal Knowledge Graph. The Eval Said No.

We Almost Deployed a Temporal Knowledge Graph. The Eval Said No.

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7 min read
RAG Evaluation 2026: The Four Core Metrics and How to Read Them Diagnostically

RAG Evaluation 2026: The Four Core Metrics and How to Read Them Diagnostically

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4 min read
Swapping every model in a RAG

Swapping every model in a RAG

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9 min read
Building a Multi-Agent AI Pipeline That Ships: LangGraph, RAG, and Evals That Matter

Building a Multi-Agent AI Pipeline That Ships: LangGraph, RAG, and Evals That Matter

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6 min read
I Benchmarked My Homelab Memory Stack: Hybrid Search + Local Reranker Took LoCoMo from 63% to 80%

I Benchmarked My Homelab Memory Stack: Hybrid Search + Local Reranker Took LoCoMo from 63% to 80%

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9 min read
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