Atlassian puts its engineers on an AI budget as the cost of ‘tokenmaxxing’ bites

Atlassian has started giving its engineers a fixed monthly AI allowance of $500 to $2,000, capping spending to manage costs as token usage surges. The software maker, which cut 1,600 jobs to fund an AI pivot, now rations AI for remaining staff, reflecting a broader industry shift from unlimited AI use to cost-conscious budgeting.

The software maker cut thousands of jobs in the name of AI. Now it is handing the engineers who remain capped ‘AI wallets,’ a sign the industry’s token spending has become a line item to manage. Atlassian has started giving its engineers a fixed monthly allowance for artificial intelligence, a capped “AI wallet” that warns them as they near the limit and stops when the budget runs out. The move places the software company on the cost-conscious side of a growing divide over how much AI staff should be allowed to burn through. The caps are not trivial, but they are caps. Atlassian’s wallets run from $500 to $2,000 a month for research-and-development staff, with the size set by role and the option to ask for more, a structure meant to keep spending visible rather than to starve it. The company frames it as generosity with guardrails. “Atlassian provides a significant budget for our builders to leverage multiple AI tools,” a spokesperson said, casting the wallet as a way to fund experimentation without letting the bills run wild. There is an irony in the metering, and it is not a small one. Atlassian has recast itself as an “AI-first” company, cutting 1,600 jobs https://thenextweb.com/news/atlassian-is-cutting-1600-jobs-and-replacing-its-cto to fund the pivot, and earlier in the year it told a group of support staff, over video, that they would be largely replaced by AI. Now it is rationing that same AI for the people who kept their jobs. Having sold the technology as efficient enough to replace workers, the company is finding it is also expensive enough to need a budget, which is a harder line to put on a motivational slide. Coding agents that once cost pennies now run tasks that consume tokens by the million, and the practice of maximising that usage, nicknamed “tokenmaxxing,” https://thenextweb.com/news/tokenminimizing-companies-cap-employee-ai-spending has turned individual engineers into meaningful cost centres. The arithmetic explains the anxiety. A token is roughly four characters of text, and at prevailing prices of several dollars per million tokens for the leading models, an agent left to iterate on its own can run up a large bill, the kind of dynamic that has already broken the economics https://thenextweb.com/news/github-copilot-signup-pause-agentic-ai-usage-limits of tools like GitHub Copilot. Atlassian is not the first to react. Amazon quietly shut down an internal leaderboard that had turned heavy AI use into a competition, after employees gamed it by consuming tokens for their own sake. Meta went further still; the company warned some 6,000 staff that its internal AI spending in 2026 could reach into the billions, and began rolling out token budgets and controls of the kind Atlassian has now adopted. If last year’s fashion was tokenmaxxing, this year’s is its opposite, a turn toward treating AI spend as something to manage https://thenextweb.com/news/microsoft-claude-code-retreat-ai-cost rather than a badge of how forward-leaning a team is. The reversal is awkward for an industry that spent two years urging staff to use more AI. Executives who once measured adoption by token volume are now measuring it by cost per outcome, a soberer metric that fits a moment of tighter budgets. Not everyone is pulling back. Some firms still offer unlimited AI budgets as a recruiting perk and a bet on productivity, wagering that the output justifies the spend and that capping it would only slow their best engineers. That is the real disagreement beneath the wallets. No one doubts the tools are useful; the fight is over whether unlimited access produces enough extra value to be worth an unpredictable, fast-rising bill. Atlassian’s answer is a middle path. By funding multiple tools but metering their use, it is trying to keep the productivity of agentic AI while stripping out the waste, a balance the whole sector is now hunting for. Whether that produces better engineering or merely cheaper engineering is the open question. For now, a company that thinned its workforce in the name of AI is asking the survivors to watch every token, having learned that the technology it sold as a way to do more with fewer people is not, as it turns out, free. Get the TNW newsletter Get the most important tech news in your inbox each week.