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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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Three things I got wrong measuring my own cache

Three things I got wrong measuring my own cache

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11 min read
I Built an MCP Memory Server Where Code, Not the Model, Decides What Gets Stored

I Built an MCP Memory Server Where Code, Not the Model, Decides What Gets Stored

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8 min read
Debrief is not a PDF chatbot — it recovers decisions with citations

Debrief is not a PDF chatbot — it recovers decisions with citations

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2 min read
RAG Without a Vector Database: My Production Assistant Runs on MariaDB and 10 Lines of Cosine Similarity

RAG Without a Vector Database: My Production Assistant Runs on MariaDB and 10 Lines of Cosine Similarity

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2 min read
7 Retrieval Checks for Fixing Wrong Ask-Your-Docs Chatbot Answers

7 Retrieval Checks for Fixing Wrong Ask-Your-Docs Chatbot Answers

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6 min read
LangChain vs LlamaIndex vs Chonkie: same 94-page PDF

LangChain vs LlamaIndex vs Chonkie: same 94-page PDF

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7 min read
Not All Multilingual Embedding Models Are Equal — Testing 5 of Them

Not All Multilingual Embedding Models Are Equal — Testing 5 of Them

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14 min read
From a Test-Suite Trace to a Search Signal: the Bootstrap Pipeline Story

From a Test-Suite Trace to a Search Signal: the Bootstrap Pipeline Story

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9 min read
macOS Keychain Support for Electron Apps: A Game Changer for Secure A…

macOS Keychain Support for Electron Apps: A Game Changer for Secure A…

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2 min read
From Demo to Production: The Guardrails That Make an AI Agent Safe to Ship

From Demo to Production: The Guardrails That Make an AI Agent Safe to Ship

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4 min read
6 Node.js Tenant Guardrails for Cheap Invoice RAG (Count Embeddings and LLM Spend)

6 Node.js Tenant Guardrails for Cheap Invoice RAG (Count Embeddings and LLM Spend)

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8 min read
RAG - Async Pipelines, MCP

RAG - Async Pipelines, MCP

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3 min read
My AI agent failed obvious tasks, and 49% fewer retrieval misses changed how I debugged it

My AI agent failed obvious tasks, and 49% fewer retrieval misses changed how I debugged it

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6 min read
From CAN Bus to RAG Pipelines:: Why I build?

From CAN Bus to RAG Pipelines:: Why I build?

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3 min read
I described 1,245 tables with an LLM and retrieval got worse

I described 1,245 tables with an LLM and retrieval got worse

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Comments 67
8 min read
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