AI
What I use every day, and how much.
Models
Token share, last 30 days
Harnesses
Token share, last 30 days
tstack
Private for now
My own Michelin kitchen, as poteto calls it: the skills and rules that make agents write code, review PRs and ship features the way I would. When I correct an agent, the fix becomes a rule, a check or a skill, so I don't have to say it twice.
Inspired by poteto's pstack.
- code-like-thalles
- review-pr
- babysit-pr
- correct
- improve-skills
What I used before
How I got to the setup above, in order.
- GitHub CopilotWhere everyone started. It was revolutionary, and then it barely improved. GitHub fumbled the lead.
- SupermavenLike Copilot, but a lot faster and with much better predictions.
- CursorWhere I really started using AI, and tokens. Quick edit first. I ignored the sidebar at the start, then it became my default.
- Claude CodeI flirted with it, but I prefer tools that wrap it. Opus also scored better inside Cursor than inside Claude Code.
- OpenCodeMy main for a while, because I like jumping between models.
- Cursor, againBack for their agents in the browser.
- T3 Code, the first timeI tried it while looking for something that worked with a remote dev machine, which I was already doing by February. It wasn't there yet.
- MaestriI loved it and daily drove it for about two months. In the end it was too complicated, and I got lost in my own workflows.
- T3 Code, nowI came back for the sidebar, which is amazing. It's open source, runs a bunch of harnesses, performs better, and remote dev on it is great. It's what I use every day.
How much AI I use
Most of my code is written with agents now. This is how many tokens that takes.
Tokens per daySep 29 to Oct 28
- Tokens, all time
- 62.5B
- Output, 30 days
- 107.7M
- Sessions, all time
- 3,205
- Top model, all time
- Claude Opus 5.5
Cost at API list price would be $52,526. I pay a subscription, not that. Tracked with tokenmaxxing.sh.