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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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Two audits of my own knowledge graph found two unrelated silent failures

Two audits of my own knowledge graph found two unrelated silent failures

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4 min read
Running a Whole RAG Agent Offline: LangGraph + Ollama + Embedded Qdrant (Zero API Keys)

Running a Whole RAG Agent Offline: LangGraph + Ollama + Embedded Qdrant (Zero API Keys)

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5 min read
My RAG Benchmark is lying to me

My RAG Benchmark is lying to me

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5 min read
My RAG Benchmark is lying to me

My RAG Benchmark is lying to me

1
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5 min read
How I Built a Persona Chat Agent and Fought Hallucination — A RAG Story

How I Built a Persona Chat Agent and Fought Hallucination — A RAG Story

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6 min read
How I Built a RAG System Over more than 100 USCIS Administrative Appeals Office Decisions with Gemini

How I Built a RAG System Over more than 100 USCIS Administrative Appeals Office Decisions with Gemini

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8 min read
SWIRL Community 4.5 Update

SWIRL Community 4.5 Update

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1 min read
Stop Asking the LLM Whether Its Source Is Real

Stop Asking the LLM Whether Its Source Is Real

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3 min read
hack with Hyd 2.0

hack with Hyd 2.0

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1 min read
I built a private Copilot alternative that never lets your data leave your Microsoft 365 tenant

I built a private Copilot alternative that never lets your data leave your Microsoft 365 tenant

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2 min read
CAG: The Simpler Way to Ground Your LLM

CAG: The Simpler Way to Ground Your LLM

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3 min read
Evaluating Large Language Models: The Pitfall of Overfitting in RAG

Evaluating Large Language Models: The Pitfall of Overfitting in RAG

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2 min read
Evaluating Large Language Models: The Overfitting Problem

Evaluating Large Language Models: The Overfitting Problem

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2 min read
Building a RAG System from Scratch — Design Decisions Explained

Building a RAG System from Scratch — Design Decisions Explained

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4 min read
Building a RAG System from Scratch — Wrap-up and What Comes Next

Building a RAG System from Scratch — Wrap-up and What Comes Next

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4 min read
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