How an Agent Finds Your Docs, and Which Files It Actually Reads
Five file conventions claim to be the standard for AI agents. Here is what each one answers, who really reads it, and the evidence behind both claims.
Retrieval and RAG08
Subject · 6 posts
information retrieval
Before You Retrieve Anything, Someone Has to Read the PDF
Every retrieval method assumes clean structured text. Getting it out of a PDF is its own problem, and Docling is the 2026 answer worth knowing.
Retrieval and RAG07
Several Retrievers, One Small Machine
How to run keyword, dense, fusion and reranking together on modest hardware: where the memory actually goes, and which famous constants are folklore.
Retrieval and RAG06
PageIndex: Retrieval With No Vectors At All
PageIndex indexes a document as its own table of contents and lets a model walk the tree. No embeddings, no chunking, and a route you can show a reader.
Retrieval and RAG04
When Your Knowledge Base Should Be a Graph
GraphRAG turns a corpus into entities, communities and LLM-written reports so it can answer whole-corpus questions that top-k retrieval structurally cannot.
Retrieval and RAG02
Retrieval Metrics Demystified: From BM25 Baselines to EM@5 & Answer F1
What BM25, Recall@k, answer-in-context rate and token F1 actually measure, which number to fix first, and how to compute them without fooling yourself.
Retrieval and RAG01