Amazon has advised software engineers against excessive AI use, warning that higher token consumption does not ensure productivity.
Why Is Amazon Discouraging ‘Tokenmaxxing’?
Amazon has urged employees to reconsider the practice of “tokenmaxxing”, in which workers use artificial intelligence tools as extensively as possible, amid concerns about rising costs and whether greater AI consumption translates into better performance.
The guidance forms part of an internal memorandum outlining the company’s AI usage principles for software engineers. The document was circulated internally in September and published on Amazon’s website on October 27, 2026.
Amazon said measures such as token consumption, AI adoption rates and the number of code changes or reviews are deeply flawed indicators of organisational performance. Excessive reliance on these measurements, it argued, can increase costs and introduce unnecessary complexity.
However, the company has not advised employees to disregard such metrics entirely. Instead, it has called for careful judgement when using them to assess individual and organisational performance.
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How Does Amazon Want Employees to Measure AI Productivity?
The company has emphasised that long-term outcomes should take precedence over the volume of AI tools used.
In its memorandum, Amazon discouraged engineers from using AI where it offers no meaningful advantage for a particular task. It said employees should be able to identify situations where existing AI tools do not improve their work.
The guidance also addresses the changing responsibilities of software engineers and managers as AI becomes more deeply integrated into software development.
Amazon acknowledged that many aspects of AI-driven engineering remain uncertain but maintained that the technology would play a central role in future software engineering practices. Despite discouraging excessive consumption, Amazon has not introduced formal limits on employees’ AI token usage.
In May 2026, the company reportedly discontinued an internal leaderboard after discovering that some employees were consuming additional AI tokens to improve their rankings.
Why Are Technology Companies Reconsidering AI Spending?
Amazon’s guidance comes amid a broader reassessment of AI expenditure across major technology companies. AI tokens are units used to measure the consumption of AI systems. Although token prices have been declining, the overall cost of completing certain tasks has increased as providers move from flat subscriptions towards usage-based pricing.
This shift has made expenditure less predictable, particularly when the amount of AI processing required for individual tasks varies considerably.
Some companies have responded by limiting employee token consumption, while others have adopted cheaper open-source AI models for selected activities.
The changing approach reflects concerns that measuring productivity primarily through AI usage can encourage greater expenditure without demonstrating corresponding improvements in work quality or efficiency.
What Does This Mean for Amazon’s Workforce?
The revised guidance comes as Amazon continues to assess how AI will reshape its operations and workforce. Chief Executive Andy Jassy has previously said that AI could change the scope and speed of everyday work, potentially reducing the company’s corporate workforce over the coming years through automation. He has also acknowledged that the technology could create other jobs.
Amazon cut fewer than 1,000 white-collar positions earlier in October, primarily within its retail division. These reductions followed a larger round of 30,000 job cuts that began in 2025 and continued into January 2026.
The company has not directly linked those reductions to its latest guidance on AI token consumption.
The420 Insight: Amazon’s approach highlights a shift from measuring how frequently employees use AI towards assessing whether the technology delivers meaningful results. As usage-based costs become harder to predict, companies are increasingly examining whether additional AI consumption produces measurable benefits.
