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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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Why I Kept Search Scope Inside a Single Supabase RPC

Why I Kept Search Scope Inside a Single Supabase RPC

Comments 2
8 min read
Fix Your Search, Fix Your RAG Output

Fix Your Search, Fix Your RAG Output

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6 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
Vector Split by Chunk: Why My Retrieval Stops at the Boundary I Drew

Vector Split by Chunk: Why My Retrieval Stops at the Boundary I Drew

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7 min read
PDF Parsing Is the Hidden Bottleneck in Your RAG Pipeline

PDF Parsing Is the Hidden Bottleneck in Your RAG Pipeline

Comments 1
3 min read
Coverage Before Creativity: The RAG Gate That Keeps My Blog Pipeline Honest

Coverage Before Creativity: The RAG Gate That Keeps My Blog Pipeline Honest

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8 min read
Where Does RAG Actually Cost You Money? (Episode 2)

Where Does RAG Actually Cost You Money? (Episode 2)

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Comments 2
7 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
AI builder essentials: tokens, context windows and RAG 101

AI builder essentials: tokens, context windows and RAG 101

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1 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
Stop Sending the Raw User Prompt Straight to Your Retriever

Stop Sending the Raw User Prompt Straight to Your Retriever

Comments 3
2 min read
#Neo4j vs pgvector vs MongoDB vs Milvus vs Pinecone vs FAISS: The Complete Vector Database Guide for 2026

#Neo4j vs pgvector vs MongoDB vs Milvus vs Pinecone vs FAISS: The Complete Vector Database Guide for 2026

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15 min read
How to Evolve a Linear LangChain RAG Pipeline into a Stateful, Multi-Agent Consensus Architecture

How to Evolve a Linear LangChain RAG Pipeline into a Stateful, Multi-Agent Consensus Architecture

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1 min read
Parsing documents for air-gapped RAG: no cloud, no JVM, no Python

Parsing documents for air-gapped RAG: no cloud, no JVM, no Python

Comments 5
5 min read
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