6th February 2026
When I want to quickly implement a one-off experiment in a part of the codebase I am unfamiliar with, I get codex to do extensive due diligence. Codex explores relevant slack channels, reads related discussions, fetches experimental branches from those discussions, and cherry picks useful changes for my experiment. All of this gets summarized in an extensive set of notes, with links back to where each piece of information was found. Using these notes, codex wires the experiment and makes a bunch of hyperparameter decisions I couldn’t possibly make without much more effort.
— Karel D'Oosterlinck, I spent $10,000 to automate my research at OpenAI with Codex
Recent articles
- Datasette Apps: Host custom HTML applications inside Datasette - 18th June 2026
- GLM-5.2 is probably the most powerful text-only open weights LLM - 17th June 2026
- Publishing WASM wheels to PyPI for use with Pyodide - 13th June 2026