tokenmaxxing
In plain wordsUsing as much AI as possible — huge prompts, long sessions, many agents at once — mainly to rank high on workplace measures of how much AI people use.
The practice of maximizing one's consumption of AI tokenstoken, n.: The small chunk of text an AI language model reads and writes — often a word, part of a word or a punctuation mark. AI usage, limits and prices are counted in tokens. — through long prompts, extended coding sessions and many parallel agents — in order to rank highly on employer metrics of AI adoption, treating token spend as a proxy for productivity. It flourished in 2026 as companies tied AI use to performance expectations: an internal leaderboard at Meta that ranked employees by token consumption drew wide coverage before it was taken down, and similar pressure to maximize usage was reported at other large firms, including Amazon. Critics compare it to judging programmers by lines of code, noting that it rewards busywork, inflates AI bills and invites careless code.
He's not shipping more, he's tokenmaxxing: six agents refactoring the same folder all night.
Origin
Formed with the slang suffix '-maxxing' (to maximize something obsessively, as in 'looksmaxxing'). The word spread in April 2026 amid reports of AI-usage leaderboards at large technology companies; Gergely Orosz's Pragmatic Engineer newsletter called it a 'weird new trend' that month.
Usage note
Parallel in form to benchmaxxingbenchmaxxing, n.: Slang for tuning an AI model to score as high as possible on well-known tests, even when this does not make it genuinely better at real-world tasks., which games evaluations of models; tokenmaxxing games evaluations of people — a textbook case of Goodhart's lawGoodhart's law, n.: The rule of thumb that once a number is used as a target, people or AIs find ways to push it up that no longer reflect what it was meant to measure..
Related
- benchmaxxingbenchmaxxing, n.: Slang for tuning an AI model to score as high as possible on well-known tests, even when this does not make it genuinely better at real-world tasks.
- Goodhart's lawGoodhart's law, n.: The rule of thumb that once a number is used as a target, people or AIs find ways to push it up that no longer reflect what it was meant to measure.
- workslopworkslop, n.: AI-generated work that looks polished but does not actually get the job done, quietly passing the real effort to whoever receives it, who must then puzzle it out or start over.
- AI hypeAI hype, n.: Exaggerated claims about what AI can do or will soon do, made to attract money, attention or customers, which can mislead the public and policymakers.
- tokentoken, n.: The small chunk of text an AI language model reads and writes — often a word, part of a word or a punctuation mark. AI usage, limits and prices are counted in tokens.
- agentic codingagentic coding, n.: Writing software by directing AI agents that plan, edit and test code themselves, with the human acting more as a reviewer and manager than as the person typing every line.
Sources
- Orosz, G. (2026). The Pulse: 'Tokenmaxxing' as a weird new trend. The Pragmatic Engineer, April 2026. blog.pragmaticengineer.com/the-pulse-tokenmaxxing-as-a-weird-new-trend
- The Decoder (2026). Meta employees compete for token consumption on an internal AI leaderboard. the-decoder.com/meta-employees-compete-for-token-consumption-on-an-internal-ai-leaderboard