ai-research-os-workshop

Building Your Own AI Research OS Workshop

This is the repo for the talk at the AI Engineer World's Fair conference, presented by Louis-François Bouchard ( X · LinkedIn ) and Paul Iusztin ( X · LinkedIn ).

I'm always losing my research.

5,000+ notes in Obsidian, 5,000+ highlights in Readwise, plus Notion and Google Drive — growing ~250 files a month. And every research session still starts from zero: paste the same links into Codex, watch it rebuild context on the fly, then lose all of it when the chat ends.

Access to information was never the bottleneck. Reusing it was.

AI Research OS turns your Second Brain into a living research memory your agents maintain — research that compounds over weeks, months, and years instead of dying in a conversation.

Codex or Claude gives you an answer. This gives your harness a reusable research memory:

• raw/ - copied or fetched source material
• wiki/sources/ - per-source summaries
• wiki/concepts/, wiki/entities/, wiki/comparisons/ - reusable synthesis pages
• wiki/overview.md and wiki/synthesis.md - the current thesis
• index.yaml and index.md - the catalog future agents read first
• log.md and wiki/open-questions.md - what happened and what to research next

The point is not to replace Codex. The point is to stop re-researching the same topic every week.

What this is

AI Research OS is a set of local AI skills for building and querying a persistent research wiki from your own sources: