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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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Building a Safety-First RAG Triage Agent in Python

Building a Safety-First RAG Triage Agent in Python

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7 min read
From RAG to Agentic AI Systems: What’s Actually Changing in Modern Full-Stack Development

From RAG to Agentic AI Systems: What’s Actually Changing in Modern Full-Stack Development

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3 min read
RAG chunking strategy that beats "smarter" alternatives

RAG chunking strategy that beats "smarter" alternatives

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4 min read
A Self-Hosted Web Content Extraction API

A Self-Hosted Web Content Extraction API

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5 min read
Prompting vs RAG vs Fine-Tuning: When to Use Each (A Developer's Decision Framework)

Prompting vs RAG vs Fine-Tuning: When to Use Each (A Developer's Decision Framework)

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9 min read
RAG Series (23): Multimodal RAG — Images and Tables Can Be Retrieved Too

RAG Series (23): Multimodal RAG — Images and Tables Can Be Retrieved Too

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7 min read
Building KernelMind Part 3: Evaluation, Retrieval Ablations, RAGAS, and Turning The Project Into Something Measurable

Building KernelMind Part 3: Evaluation, Retrieval Ablations, RAGAS, and Turning The Project Into Something Measurable

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6 min read
Why Search-Enabled LLMs Still Get Numbers Wrong

Why Search-Enabled LLMs Still Get Numbers Wrong

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2 min read
Understanding RAG by Building a ChatPDF App: Smarter Chunking & Context Optimization (Part 3)

Understanding RAG by Building a ChatPDF App: Smarter Chunking & Context Optimization (Part 3)

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4 min read
Building Production RAG Pipelines: 3 Lessons from My First Year

Building Production RAG Pipelines: 3 Lessons from My First Year

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3 min read
The Air Canada Chatbot Lawsuit Was a Chunk Quality Problem, Not an AI Problem

The Air Canada Chatbot Lawsuit Was a Chunk Quality Problem, Not an AI Problem

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7 min read
Claude Code Plugins for Design Systems & Agent Orchestration for Real Workflows

Claude Code Plugins for Design Systems & Agent Orchestration for Real Workflows

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3 min read
Building an Evaluation Harness for Financial RAG: What I Learned About LLM-as-Judge Calibration

Building an Evaluation Harness for Financial RAG: What I Learned About LLM-as-Judge Calibration

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4 min read
The gap between detecting hallucinations and handling them

The gap between detecting hallucinations and handling them

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2 min read
How to Actually Design an AI Agent: Tools and the Starting Loop (Part 2)

How to Actually Design an AI Agent: Tools and the Starting Loop (Part 2)

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5 min read
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