Chunking Technique Research

June 9, 2026

AI   Python  

After building RAG systems for technical books, I kept asking which chunking strategy actually retrieves better. I built a research platform to answer that with real vector search, LLM-as-judge ground truth, and metrics such as NDCG, MAP, and MRR. I compare fixed-length and overlap splitters with heading-aware and linguistically scored approaches. Some of this is still a heuristic, not a settled result.

Consuming Textbooks

May 28, 2026

AI   Learning  

I never finished technical textbooks by reading them cover to cover. This article describes how I use an LLM as a chapter-by-chapter study partner, with room for side quests and real code along the way. The point is not to hand off the understanding. It is to keep the doing in the loop so the material sticks.

Vibe Coding - Style Over Substance

January 1, 2026

AI  

AI can whisper an elegant function into a codebase, and that can hide a shallow understanding of the work. This article is my take on vibe coding, style over substance, and using AI as a sidekick rather than a replacement for the craft. I draw a line from the sci-fi companions I grew up with to how I actually write software.

HAL - Highly Adaptable Learning AI

March 18, 2025

Python   AI  

HAL is a retrieval-augmented generation assistant for technical books, with a WarGames-style terminal UI. I built it to ingest compiler and systems texts, chunk and embed them, store them in Qdrant, and answer questions from that store. This article is the stack, the architecture, and what I learned. It is part nostalgia project and part a real attempt to make those books searchable.