59.2 billion tokens in 173 days produced 90 shipped launches, 4,627 commits and a live game with a real user base, for $1,200.
The constraint was never the machine. It was how fast one person can decide.
I spent fifteen years as a creative strategist in brand and culture, passing every idea to a creative team or a client to get it made. AI tooling collapsed that conveyor belt. The person with the taste can now build the thing, and this deck is the meter reading from six months of doing exactly that.
Tokens logged between 15 January and 6 July 2026. The counter is public and updates daily at mikelitman.me/token-usage, with the raw numbers in data.json.
Not a demo week or a hackathon burst. A working practice, logged session by session, still running when the write-up shipped.
Fifty-nine billion tokens sounds like a machine typing day and night. Mostly it is not.
The bulk of the volume is cache reads: the same files and conversation loaded again and again as long sessions continue.
The record is honest about its own gaps. The first weeks predate proper instrumentation, so 19.1% of the history (33 early days) is spread from archive totals rather than measured per day, and the dashboard marks that estimate zone visibly instead of smoothing it away. A second, independently coded tracker over the same raw sources agrees with the headline to within 2.1%.
Tokens are the fuel, not the point. Over the same 173 days, the public launch log at mikelitman.me/all-projects recorded what the fuel actually moved.
Absurd numbers by hand-tool standards, and that is the point. Token volume is what it costs to give a machine enough context to do real work on a real codebase. The economics only look strange until you stop pricing the fuel and start pricing the freight.
The six months were not a flat line. A launch week runs at multiples of the trailing median, then the line drops back while real users, cron jobs and monitoring take over. The meter sees both.
The quiet weeks matter more than the peaks. That is where the automated pipelines, scheduled agents and watchdogs earn their keep, because output continues while attention is elsewhere. Anyone can produce a big number in a demo week; the shape of a maintenance week is what separates a working practice from a stunt.
Actual spend over the six months. Roughly the cost of a phone contract, for the volume of work above.
That figure is an equivalence, not a saving; nobody would have bought those tokens at list price, and the dashboard labels it exactly that way.
Instruments drift. The discipline is building the gauge that catches your own gauge lying.
Working with AI at this volume turns one person into a very small institution, and institutions need infrastructure. Everything that broke produced a rule, and the rules compound: verified numbers only, never from memory; every deploy gated on contrast and mobile checks; regression gates on anything a pipeline publishes; and a persistent memory system so the five-hundredth session starts smarter than the first.
On its own, yes. A big number with nothing chained to it proves enthusiasm, not output. And one case proves nothing about anyone else.
Measured, not remembered. That is the whole method, and it fits in three words.
Asked for a one-line verdict on the six months, unedited: "this is how it's going to be now i'm almost certain of it - being the orchestrator and the agent manager is going to need to be a way of working that everyone knows how to do"
On pace to cross 100 billion around 29 August 2026 · mikelitman.me · hello@mikelitman.me