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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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I Built a RAG App, Then Asked It What Car I Like. It Didn't Know.

I Built a RAG App, Then Asked It What Car I Like. It Didn't Know.

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6 min read
Why RAG Isn't Enough: Building RationaleVault for Cognitive Continuity

Why RAG Isn't Enough: Building RationaleVault for Cognitive Continuity

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4 min read
Building RAGEval: My Journey from Problem to Production Foundation in 2 Days

Building RAGEval: My Journey from Problem to Production Foundation in 2 Days

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9 min read
How to move from an LLM demo to a production-ready healthcare AI agent

How to move from an LLM demo to a production-ready healthcare AI agent

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6 min read
RAG Explained: Give an LLM Your Own Knowledge

RAG Explained: Give an LLM Your Own Knowledge

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1 min read
Chain-of-Verification: Make an LLM Fact-Check Itself

Chain-of-Verification: Make an LLM Fact-Check Itself

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1 min read
Bedrock Managed Knowledge Base: Anatomy of a Managed RAG Pipeline

Bedrock Managed Knowledge Base: Anatomy of a Managed RAG Pipeline

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10 min read
How to Use Deep Agents with Azure Cosmos DB – Plan, act, and verify against operational data

How to Use Deep Agents with Azure Cosmos DB – Plan, act, and verify against operational data

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10 min read
Contract Intelligence on AWS: Field-Notes Architecture

Contract Intelligence on AWS: Field-Notes Architecture

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10 min read
Building a Free AI PDF Assistant: How I Solved Parsing Issues and Minimized LLM Costs

Building a Free AI PDF Assistant: How I Solved Parsing Issues and Minimized LLM Costs

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3 min read
Adding streaming to my RAG pipeline — three SDKs, three different APIs

Adding streaming to my RAG pipeline — three SDKs, three different APIs

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5 min read
Phase 2: Embeddings & Semantic Search

Phase 2: Embeddings & Semantic Search

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10 min read
From Code to Governance: The Complete Guide to LLM Token Optimization

From Code to Governance: The Complete Guide to LLM Token Optimization

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8 min read
RAG in production: the failure modes nobody warns you about

RAG in production: the failure modes nobody warns you about

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3 min read
When AI Is Confidently Wrong, Who's Responsible?

When AI Is Confidently Wrong, Who's Responsible?

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3 min read
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