Amazon employees are tokenmaxxing to inflate AI usage scores amid intense adoption pressure

Amazon employees are "tokenmaxxing" due to pressure to use AI tools

Amazon employees are using an internal AI tool to automate non-essential tasks in a bid to show managers they are using the technology more frequently. The Seattle-based group has started to widely deploy its in-house "MeshClaw" product in recent weeks, allowing employees to create AI agents that can connect to workplace software and carry out tasks on a user's behalf, according to three people familiar with the matter. Some employees said colleagues were using the software to automate additional, unnecessary AI activity to increase their consumption of tokens -- units of data processed by models. They said the move reflected pressure to adopt the technology after Amazon introduced targets for more than 80 percent of developers to use AI each week, and earlier this year began tracking AI token consumption on internal leader boards. "There is just so much pressure to use these tools," one Amazon employee told the FT. "Some people are just using MeshClaw to maximize their token usage." Amazon has told employees that the AI token statistics would not be used in performance evaluations. But several staff members said they believed managers were monitoring the data. "Managers are looking at it," said another current employee. "When they track usage it creates perverse incentives and some people are very competitive about it." Silicon Valley groups are pushing to increase adoption of generative AI tools, as companies seek to demonstrate returns on vast spending commitments to AI infrastructure and embed the technology more deeply into day-to-day work. Amazon this year is expected to spend $200 billion in capital expenditure, the vast majority of which will go towards AI and data centre infrastructure. The e-commerce group had posted team-wide statistics on AI usage by its staff, but recently limited access so that only employees themselves and managers can view their stats. Managers are discouraged from using token use to measure performance, according to a person familiar with the matter. Meta employees have similarly engaged in so-called "tokenmaxxing" to improve their standing on internal leader boards. The MeshClaw tool that some employees have used to increase their statistics was inspired by OpenClaw, which became a viral sensation in February. OpenClaw allows users to run agents locally on their own hardware, including computers and laptops. Amazon's MeshClaw can initiate code deployments, triage emails and interact with apps such as Slack, according to people familiar with the matter. The company said in a statement that the tool enabled "thousands of Amazonians to automate repetitive tasks each day" and was one example of the group "empowering teams" to experiment and adopt AI tools. "We're committed to the safe, secure and responsible development and deployment of generative AI for our customers," it added. More than three dozen Amazon employees worked on the in-house tool, according to internal documents. One recent memo describing the bot said: "It dreams overnight to consolidate what it learned, monitors your deployments while you're in meetings and triages your email before you wake up." Multiple Amazon employees said they were concerned about the security risks of an AI tool that was granted permission to act on a user's behalf. This risks situations where the agent may make errors or undertake unintended actions. "The default security posture terrifies me," one employee said. "I'm not about to let it go off and just do its own thing."

Amazon employees admit to using AI unnecessarily to pump up internal usage scores -- workers complain of intense pressure to use AI tools

Employees at Amazon, Meta, and Microsoft have been gaming AI usage metrics. Amazon is the latest hyperscaler where employees have been caught inflating AI token consumption to hit internal usage targets, following similar behavior documented at Meta and Microsoft last month, the Financial Times reports. The company set targets requiring more than 80% of its developers to use AI tools each week and tracked consumption on internal leaderboards. Some employees told FT they had been using MeshClaw, an in-house agent platform that can initiate code deployments, triage emails, and interact with Slack to maximize their token numbers. Amazon said usage statistics would not factor into performance evaluations, but multiple employees said they believed managers were monitoring the data. One said there was "so much pressure to use these tools," another described how tracking created "perverse incentives." The practice -- dubbed "tokenmaxxing" -- has become widespread enough to generate its own vocabulary and leaderboards, but beyond workplace culture, if a meaningful share of AI consumption is performative, how reliable are the demand figures that hundreds of billions in AI infrastructure procurement are being allocated against? Combined 2026 capex from Amazon, Microsoft, Alphabet, and Meta is tracking between $650 billion and $700 billion, with some Wall Street projections exceeding $1 trillion for 2027, and every hyperscaler has told investors that inference capacity is being absorbed as fast as it can be deployed. Internal developer consumption is obviously part of that absorption, and it sits alongside paying external customers in the usage data that informs the likes of capacity planning, GPU orders, HBM procurement, and power infrastructure. Tokenmaxxing doesn't mean the demand is fabricated -- enterprise AI adoption is broadening, and inference workloads are scaling into production -- but there's a distinction between adoption and consumption intensity. The former is a durable driver of demand, whereas the latter is gameable, and it's currently being amplified by the incentive structures that these companies built. The water is further muddied by reports that AI is more expensive than actual workers. Meta's internal leaderboard lasted days after public exposure, and Amazon recently restricted visibility of team-wide usage statistics. And when measurement shifts, the consumption intensity they incentivized will shift with them. Nvidia CEO Jensen Huang has highlighted per-engineer token consumption as a key metric, stating he'd be "deeply alarmed" if a $500,000-a-year engineer was not consuming at least $250,000 in tokens. Nvidia's inference growth obviously depends on that consumption being a productive workload that persists and compounds because every inflated token is real GPU time. Angie Jones, formerly VP of engineering for AI tools at Block, told LeadDev she expected the industry to pivot toward measuring efficient token usage rather than celebrating volume. In a cycle where GPU orders and power commitments are being placed years in advance, the quality of the demand projections behind them matters. The hyperscalers are building for a world where every knowledge worker consumes hundreds of thousands of dollars in annual compute. Whether that consumption proves productive or performative will determine how much of this year's $700 billion generates durable returns. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds.

Amazon staff use AI tool for unnecessary tasks to inflate usage scores

Amazon employees are using an internal AI tool to automate non-essential tasks in a bid to show managers they are using the technology more frequently. The Seattle-based group has started to widely deploy its in-house "MeshClaw" product in recent weeks, allowing employees to create AI agents that can connect to workplace software and carry out tasks on a user's behalf, according to three people familiar with the matter. Some employees said colleagues were using the software to automate additional, unnecessary AI activity to increase their consumption of tokens -- units of data processed by models. They said the move reflected pressure to adopt the technology after Amazon introduced targets for more than 80 per cent of developers to use AI each week, and earlier this year began tracking AI token consumption on internal leader boards. "There is just so much pressure to use these tools," one Amazon employee told the FT. "Some people are just using MeshClaw to maximise their token usage." Amazon has told employees that the AI token statistics would not be used in performance evaluations. But several staff members said they believed managers were monitoring the data. "Managers are looking at it," said another current employee. "When they track usage it creates perverse incentives and some people are very competitive about it." Silicon Valley groups are pushing to increase adoption of generative AI tools, as companies seek to demonstrate returns on vast spending commitments to AI infrastructure and embed the technology more deeply into day-to-day work. Amazon this year is expected to spend $200bn in capital expenditure, the vast majority of which will go towards AI and data centre infrastructure. The ecommerce group had posted team-wide statistics on AI usage by its staff, but recently limited access so that only employees themselves and managers can view their stats. Managers are discouraged from using token use to measure performance, according to a person familiar with the matter. Meta employees have similarly engaged in so-called "tokenmaxxing" to improve their standing on internal leader boards. The MeshClaw tool that some employees have used to increase their statistics was inspired by OpenClaw, which became a viral sensation in February. OpenClaw allows users to run agents locally on their own hardware, including computers and laptops. Amazon's MeshClaw can initiate code deployments, triage emails and interact with apps such as Slack, according to people familiar with the matter. The company said in a statement that the tool enabled "thousands of Amazonians to automate repetitive tasks each day" and was one example of the group "empowering teams" to experiment and adopt AI tools. "We're committed to the safe, secure and responsible development and deployment of generative AI for our customers," it added. More than three dozen Amazon employees worked on the in-house tool, according to internal documents. One recent memo describing the bot said: "It dreams overnight to consolidate what it learned, monitors your deployments while you're in meetings and triages your email before you wake up." Multiple Amazon employees said they were concerned about the security risks of an AI tool that was granted permission to act on a user's behalf. This risks situations where the agent may make errors or undertake unintended actions. "The default security posture terrifies me," one employee said. "I'm not about to let it go off and just do its own thing."

Amazon workers are apparently 'tokenmaxxing' AI platforms to hit arbitrary usage targets

* Amazon wants 80% of its developers to be using AI every single week * The company is even tracking AI token usage via internal leaderboards * Unwilling workers are using AI where it's not necessary just to inflate figures Some Amazon employees are reportedly using the company's internal agentic AI platform, MeshClaw, to automate unnecessary or trivial parts of their work simply to boost internal AI usage metrics. This comes as company workers are being pressured from above to use more AI - Amazon wants four in five of its developers to be using the tech weekly, and has since started tracking AI token consumption on internal leaderboards. With workers adoption still relatively slow, many have turned to behavior described as 'tokenmaxxing' to artificially inflate their AI usage metrics, the Financial Times has reported. Amazon workers are pretending to use AI more than they are MeshClaw is one of the company's internal systems designed to support the adoption of AI, allowing employees to create their own AI agents to navigate software, coding, emails and other regular workflows. But workers are now said to be optimizing their usage to maximize token counts rather than useful outcomes, ultimately leading to unnecessary AI calls that are increasing Amazon's compute costs without delivering true ROI. And it's not just Amazon looking to drive AI adoption internally, with Meta, Microsoft and other companies also reportedly gamifying uptake with internal leaderboards. However, a recent study by engineering analytics firm Jellyfish (via Business Insider) reveals that, while the heaviest AI users consumed around 10x more tokens than average, they only achieved a 2x increase in productivity. Conversely, Nvidia CEO Jensen Huang said in an interview with the All-In Podcast he would be "deeply alarmed" if workers like software engineers or AI researchers didn't use half their annual salary's worth of AI tokens annually - that's $250,000 in tokens for a $500,000 worker. Follow TechRadar on Google News and add us as a preferred source to get our expert news, reviews, and opinion in your feeds.

'That doesn't sound very healthy': Amazon's reported tokenmaxxing might gamify AI usage, analyst warns | Fortune

"Tokenmaxxing" is a burgeoning trend at the hyperscalers where employers are rewarding employees for using AI the most, quantified by using tokens. While it isn't clear that the usage determines much more than brownie points at Amazon, similar behavior was reported other big hyperscalers, like Microsoft and Meta. Notably, all three of these companies are heavily invested in the very tech that they're encouraging their employees to use. Amazon even reported in their recent earnings that Anthropic's increased valuation made up nearly half of the company's profits. Gil Luria, head of technology research at brokerage D.A. Davidson, said the dynamic concerned him. "That doesn't sound very healthy," Luria told Fortune. "You get the behavior that you create the incentive for. So if you tell people they'll succeed if they use a resource more, of course they'll use it more." Luria clarified that, for him, there isn't a question that AI tools are very powerful and have the opportunity to make everyone more productive. But the "hurdle," so-to-speak, is in diffusion. "Humans are rigid in how they do things," Luria said. "So if you don't create an incentive for humans to change their behavior, try something new, most of us won't." The question is how to incentivize that change without producing gaming, a problem formalized in Goodhart's Law: "when a measure becomes a target, it ceases to be a good measure." While Amazon evidently told employees that their "tokenmaxxing" would not be a factor in their performance reviews, multiple employees told the FT that they worried managers watched it anyway. One said there was "so much pressure" to use the tools, and at that, the most. This trend doesn't seem to be confined at just Amazon. At Meta, an employee built an internal leaderboard called "Claudeonomics" that ranked the company's roughly 85,000 workers by token consumption. In a 30-day window, total usage on the dashboard exceeded 60 trillion tokens, though neither CEO Mark Zuckerberg nor CTO Andrew Bosworth ranked in the top 250. The dashboard was taken down after The Information's reporting, but Meta CTO Andrew Boswort has publicly endorsed the underlying logic. He said his best engineer was spending the equivalent of his salary in tokens but, as a result, was "5x to 10x more productive." "It's like, this is easy money," Bosworth told Forbes. "Keep doing it. No limit." The stakes for the hyperscalers are huge. Combined 2026 capital expenditure from Amazon, Microsoft, Alphabet, and Meta is already pushing $700 billion, with some Wall Street projections exceeding $1 trillion for 2027, up significantly from just under $400 billion in 2025. The companies are telling investors that their inference chips are consumed as fast they are deployed, while also engaging in what Luria called "circular activity": the same companies invest in their suppliers and customers. He added that dynamic was "part of the overhang around all of the large technology companies, especially Amazon, Google, Microsoft, Meta, Nvidia." Demand for AI is the highest it's ever been. OpenAI and Anthropic are at a combined run rate of more than $70 billion, he noted, up from roughly zero two years ago. "Those companies actually represent real economic activity," he said. "That is consumers and businesses paying for access to their model." He didn't believe the hyperscalers themselves were a disproportionate source of that revenue, any more than they're full of programmers, and programmers are using the software. "But that's true for any company."

Amazon workers are under pressure to up their AI usage -- so they're making up extraneous tasks

According to Amazon employees, the company is pushing them to incorporate more and more AI in their workflows. What exactly they should be using it for is less clear -- leaving the door open for employees to waste AI resources on unnecessary tasks. As detailed in a new report by The Financial Times, Amazon employees are reportedly using the company's new internal AI tool MeshClaw to create extraneous AI agents, not to increase productivity, but to drive up AI activity. The employees say Amazon is tracking their consumption of AI tokens, incentivizing some of their colleagues to prioritize quantity over quality when it comes to the technology. Several anonymous Amazon employees told The Financial Times that rising AI expectations are changing their workplace for the worse. "There is just so much pressure to use these tools," one Amazon worker said. "Some people are just using MeshClaw to maximize their token usage."

Enterprises Look Beyond Token Counts to Measure AI | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. Amazon employees have been using the company's internal AI tool, MeshClaw, to delegate unnecessary tasks to AI agents to inflate their token consumption scores on internal leaderboards, the Financial Times reported. The company set targets for more than 80% of its developers to use AI each week and tracked usage through leaderboards showing token consumption. "Managers are looking at it," one employee told the Financial Times. "When they track usage it creates perverse incentives and some people are very competitive about it." Meta employees engaged in the same behavior, the Financial Times noted. The term for it is tokenmaxxing. When the metric is consumption, people optimize for consumption. The token was never designed to measure business value. High token usage often reflects inefficient prompting or agentic workflow leaks rather than outcomes, PYMNTS found. CFOs who grew up with annual licenses and per-seat SaaS contracts are now on the receiving end of bills tied to model calls they can't audit or predict. Engineering decisions now directly affect spending, creating a gap between technical activity and financial visibility that finance teams haven't had to manage before, PYMNTS detailed. Salesforce learned the pricing problem firsthand. When the company introduced $2-per-conversation pricing for Agentforce in late 2024, buyers couldn't model their costs. Salesforce had 5,000 Agentforce deals in its first two quarters under that model, but only 3,000 paid. It's cycled through multiple pricing structures since. Salesforce's current answer is a unit it calls the Agentic Work Unit. An AWU is one discrete task completed by an AI agent: a prompt processed, a reasoning chain finished, or a tool invoked. Tokens measure how much an AI talks. AWUs measure what it gets done. The platform has generated 2.4 billion AWUs to date, with 771 million in the fourth quarter alone. Service agents grew 106% quarter over quarter. AI search in Slack climbed 116%. The relationship between AWUs and tokens is elastic. Routine tasks like triggering a workflow or calling an API use fewer tokens over time. Complex reasoning uses more. The goal is a high inference-to-work ratio: output tokens that produce actual results. Agentic AI will account for 30% of enterprise application software revenue by 2035, surpassing $450 billion, up from roughly 2% in 2025, Gartner forecast. Enterprise customers have pushed for predictability as AI pilots move from experimentation into production workflows, Techstrong.ai reported. Amazon's tokenmaxxing problem and Salesforce's AWU model arrive at the same question from opposite ends. One shows what happens when companies measure AI by volume. The other bets that measuring by completed work produces a more honest number. The pressure to show AI adoption isn't going away. Boards want proof, CFOs want predictability, and engineering teams are caught between the two. Token counts satisfied the first demand without addressing the second. AWUs are Salesforce's attempt to do both at once. Whether buyers accept the new unit depends on whether the agents behind it actually finish what they start. Resolving a customer inquiry, updating a record, executing a workflow autonomously, those are the outputs Salesforce is crediting. If the completion rates hold under production load, the AWU has a case. If agents stall, hand off, or require intervention at scale, the metric becomes another number to game.

Amazon Workers Say Pressure Leads to Needless AI Use | PYMNTS.com

By completing this form, you agree to receive marketing communications from PYMNTS and to the sharing of your information with our sponsor, if applicable, in accordance with our Privacy Policy and Terms and Conditions. That's according to a Financial Times (FT) report Tuesday (May 12), which said this usage of artificial intelligence (AI) for non-essential tasks is a way for staff to demonstrate to management that they are turning to the technology more often. Sources familiar with the matter told the FT that Amazon has recently started to widely use its "MeshClaw" product internally, letting workers create AI agents that can complete tasks on a user's behalf. Some employees said their coworkers were using the software to automate additional, unnecessary AI activity to boost their token consumption. They said this was in response to pressure to adopt the tech as Amazon instituted targets for more than 80% of developers to use AI each week, and earlier this year started tracking AI token consumption on what the FT report calls leaderboards, and what Amazon says are dashboards. While Amazon had told staff that the AI token statistics would not be used in performance reviews, several workers said they believed managers were keeping tabs on the data. "Managers are looking at it," said another employee. "When they track usage, it creates perverse incentives, and some people are very competitive about it." Reached for comment by PYMNTS, Amazon said the tool in question was developed by a small team and lets workers automate repetitive tasks, "freeing up time for employees to be more strategic and solve bigger customer problems." "We're committed to the safe, secure and responsible development and deployment of generative AI for our customers," the company added. "We welcome feedback from employees about their experiences with AI tools because their feedback helps us improve the quality of the tools we provide." The company said it has no central mandate that teams use AI tools, and that the company tracks token use to understand cost and efficiency but does not encourage it as a metric for developer's performance. This is playing out at a time when many workplaces are introducing AI without explaining to employees how to use it, as PYMNTS wrote Tuesday. In an interview for PYMNTS' Wage to Wallet podcast, Ingo Payments CEO Drew Edwards said that workers are hearing commentary about AI-related job loss, and assuming the worst when they don't get context from their managers. "If you're a worker and what you're hearing ... is that nobody's going to have a job in five years, that is scary stuff," he said. "But I don't think anybody should be naive enough to think that the job you're doing today is not going to be impacted."