🔍 Read the full analysis: Tokenmaxxing Meets The Real Test Of AI Outcomes At Amazon on ThorstenMeyerAI.com
Prime made for students and young adults
- Fast, free delivery for dorm and study essentials
- Prime Video and Amazon Music included
- Member-only deals
TL;DR
Amazon published updated guidance for software engineers on October 27, warning that token counts and other AI-use measures become counterproductive when treated as performance targets. The memo favors customer and business outcomes, while leaving open how teams will assess those results in practice.
Amazon’s senior engineering leaders said software engineers should be judged by the impact of their work, not by how many AI tokens they use, in guidance published October 27. The memo calls token counts and related measures deeply flawed as targets, warning they can raise costs and complexity without showing whether customers or the business benefited.
The guidance was written by Amazon’s most senior engineers and introduced by Terk Terkowitz, a vice president and distinguished engineer in the company’s stores business. It revises role guidance for software engineers across Amazon. Rather than prescribing rules for particular AI tools, the document says such rules could quickly become outdated and centers the role on impact on customers, the business and the team.
The memo identifies token usage, AI-tool adoption, code changes and code reviews as inputs that some teams have used as proxies for longer-term results. It says those measures can be useful signals, and that they currently “correlate well” with important outputs. But when used as targets rather than measurements, they can encourage unnecessary activity. The memo gives two examples: “tokenmaxxing is at odds with frugality” and measuring lines of code is at odds with Amazon’s principle of inventing and simplifying.
Its advice is not to stop using AI. Leaders are asked to examine both low and high adoption: understand why teams around the 10th percentile use the tools less, and whether those around the 90th percentile are delivering more. Engineers whose work does not benefit from current AI tools should record and share that finding. Leaders should also use the tools on production work and explain where they helped and where they did not.
Six months at Amazon
From token leaderboards to an outcomes memo
Amazon spent 2026 learning the same lesson twice: once with how its engineers use AI, once with its own AI models.
- May 2026Token leaderboards backfireFinancial Times (via The Decoder): staff give an internal agent tool pointless tasks to inflate token counts. Reported, anonymous sources.
- Late May 2026KiroRank “deprecated”Amazon spokesperson to Business Insider. SVP Dave Treadwell: “Please don’t use AI just for the sake of using AI.”
- 24 Jul 2026San Francisco AGI Lab site closesConfirmed by Amazon to GeekWire. Frontier model research continues under Pieter Abbeel.
- 28 Jul 2026Most flagship Nova models wound downBusiness Insider, people familiar: Premier, Omni, Reel, Canvas to “keep the lights on”. Amazon: models “remain one of the most important things we’re working on”.
- 14 / 30 Sep 2026Nova Sonic v1, Nova Reel, Nova Canvas reach end of lifeAWS Bedrock model lifecycle page. Requests to them now fail.
- 26 Oct 2026Anthropic files its S-1Amazon notes: $6.2 billion principal, 12% ownership cap that Amazon can waive. Anthropic commits at least $110 billion to Amazon through April 2036.
- 27 Oct 2026The memo: outcomes, not tokenmaxxingUsage and throughput metrics are “deeply flawed” as targets. “Tokenmaxxing is at odds with frugality.”
- 29 Oct 2026Amazon’s third-quarter resultsAnnounced by Amazon. Not yet published when this article went live.
Sources: Amazon engineering memo (27 Oct 2026); Business Insider (29 May and 28 Jul 2026); GeekWire (24 Jul 2026); The Decoder (12 May 2026, summarising the Financial Times); AWS Bedrock model lifecycle (read 28 Oct 2026); Anthropic S-1 (26 Oct 2026).
Powered by Thorsten Meyer AI
From AI Activity to Business Results
The guidance addresses a practical problem for companies adopting generative AI: usage is easy to count, while improved customer outcomes, productivity or quality can take longer to establish. If employees are rewarded for token volume or tool adoption alone, they may have incentives to generate activity that does not improve the work. Amazon’s warning ties that risk directly to its stated concern with frugality and simpler systems.
The memo also offers a more qualified position than a rejection of AI measurement. Amazon says adoption measures currently track with outputs that matter, while cautioning that correlation is not a reason to turn those measures into individual or team targets. Its proposed approach relies on judgment and investigation: compare teams, ask what explains differences, and examine whether higher usage produces better results.
The timing makes the memo relevant beyond internal engineering practice. Amazon is investing in AI models and services, and its third-quarter results are due October 29. The source material does not say the memo will affect those results or provide a company-wide measure of AI’s financial return. It does, however, set out the standard Amazon’s engineering leaders say should guide assessment: what changed for customers and the business, rather than how much AI activity took place.
Products Worth Considering
Samsung 27-Inch Odyssey QD-OLED G8 4K 240Hz Gaming Monitor
Samsung 27-inch Odyssey OLED G6 QD-OLED QHD Gaming Monitor
Samsung 27 Odyssey OLED G5 (G50SF) QHD QD-OLED Gaming Monitor
As an affiliate, we earn on qualifying purchases.
The Lead-Up to Amazon’s Guidance
The memo follows earlier reports about employee tracking and incentives. In May, the Financial Times reported that some Amazon employees gave an internal agent tool, MeshClaw, unnecessary tasks to raise their token counts. That account was based on reported employee information; the source material does not establish the practice as a company-wide policy. The same reporting described a target for weekly AI use and internal token leaderboards.
At the end of May, Amazon confirmed to Business Insider that a leaderboard called KiroRank had been deprecated. The company described it as an informal tracker created by a group of employees and said it was not intended to promote AI use for its own sake. The new role guidance is a separate development: the company has now published an official engineering framework that distinguishes measuring AI activity from making it a performance goal.
The source material also compares Amazon’s in-house Nova models with its investment in Anthropic. It says Business Insider reported that most flagship Nova models were moved to maintenance in July, and that AWS lifecycle listings show Nova Canvas, Nova Reel and the first Nova Sonic retired. It cites Amazon’s June 30 filing as valuing its Anthropic holdings at about $190 billion after roughly $18 billion invested. Those figures and the interpretation of the two bets come from the supplied source; they do not establish that the engineering memo was prompted by either development.
““Tokenmaxxing is at odds with frugality.””
— Amazon engineering memo
How Amazon Will Judge AI Impact
The memo does not specify a single replacement score or a uniform method for proving that AI improved results. It acknowledges that long-term outcomes are slow and difficult to measure, but the source material does not describe how managers will weigh customer impact, business results, engineering quality or team contributions in individual reviews.
It is also unclear how consistently the guidance will be applied across Amazon’s engineering teams, or whether the company will publish follow-up data showing how AI adoption relates to results. Earlier reports about token tracking and employee behavior include accounts attributed to unnamed workers; they should not be treated as proof that all teams used leaderboards or inflated usage. The memo itself says adoption measures correlate with important outputs today, but provides no figures or time period for that relationship.
The supplied material gives financial and product details about Amazon’s Nova models and Anthropic investment, but it does not establish a direct connection between those developments and the new engineering policy. It also provides no third-quarter results; those were scheduled for the day after the memo’s publication.
Amazon’s Results and Policy in Practice
Amazon is scheduled to report third-quarter results on October 29. Those results may offer information about the company’s broader business and AI investments, but the source material does not say they will quantify the productivity impact of the engineering guidance or provide a direct scorecard for AI use.
For the policy itself, the next test will be how engineering leaders apply the memo’s instructions: whether they examine the reasons for low adoption, check whether heavy users deliver better work, and document cases where current tools do not help. The guidance places responsibility on leaders to use AI on production tasks and explain the difference between useful and unhelpful applications. No implementation timeline or reporting mechanism is given in the source material.
Key Questions
What did Amazon announce on October 27?
Amazon published revised software-engineering role guidance saying work outcomes should matter more than AI usage levels. It warns against using token counts and similar activity measures as performance targets.
Is Amazon telling engineers to stop using AI?
No. The memo does not reject AI adoption. It says adoption measures currently correlate with important outputs, but cautions against treating usage as a goal without checking whether it improves the work.
What does “tokenmaxxing” mean here?
It refers to using an AI tool in ways that increase token counts without a useful work outcome. The memo says that behavior conflicts with Amazon’s principle of frugality.
What does Amazon suggest measuring instead?
The guidance centers on impact on customers, the business and the team. It asks leaders to investigate differences in AI adoption and determine whether heavier use produces better results, rather than relying on a single activity score.
When will Amazon report its third-quarter results?
The source material says Amazon’s third-quarter results were scheduled for October 29, 2026, two days after the engineering memo was published.
Source: ThorstenMeyerAI.com
