• Amazon shifts AI focus to business impact, not just raw usage, in new developer guidelines.
• The company warns that AI metrics can create bad incentives, including “tokenmaxxing.”
• Managers are told to examine teams at both the highest and lowest levels of AI adoption.

Amazon just issued new guidelines for software engineers in the AI era: Prioritize business outcomes over raw usage.

Terk Terkowitz, Amazon's vice president and distinguished engineer, said in a memo published Tuesday that AI is changing software development more quickly and fundamentally than earlier shifts such as cloud computing. But engineers should be judged by their impact on customers and the business, he wrote, not simply how much they use AI.

"We all need to embrace this change and take the time to learn, or we risk being left behind," Terkowitz said.

AI coding tools and agents are upending the software industry and changing what it means to be a coder. Amazon calls this the "era of the Renaissance Developer," where human judgement and machine intelligence combine to create new products and services faster and more efficiently.

"This is a time of change for our industry, and a time of change for what it means to be a software engineer," Terkowitz wrote in the memo.

The updated guidelines reflect Amazon's growing effort to make AI adoption part of how it assesses engineers and engineering managers. The company has tracked measures including AI usage, token consumption, and lines of code internally, and used leaderboards to rank teams by some of those metrics.

But the memo warns that using such measures as targets can produce bad outcomes, including "tokenmaxxing" rather than better software or customer experiences.

"Using these metrics could, if used as a target instead of a measure, drive negative outcomes," Terkowitz wrote in the memo.

Amazon has been experimenting with ways to measure and encourage AI use across its engineering organization.

Earlier this year, the company was tracking engineers's use of internal AI tools and some teams used leaderboards tied to measures such as token consumption. The programs created friction among some employees, who worried that pressure to use AI could reward wasteful activity rather than productive work.

The new guidance offers Amazon's clearest public acknowledgment of that risk. Rather than lay out a detailed AI playbook that could quickly become obsolete, Amazon said its revised developer guidelines focus on long-term impact on customers and the business.

Still, the company said AI should be "at the center of software engineering practice" and urged engineers to incorporate the technology into their daily work.

Leaders are expected to use AI tools on production work themselves, understand where they help and where they fall short, and explain that judgment to their teams, according to the memo.

Terkowitz said Amazon has found that metrics such as token use, AI-tool adoption, and code reviews can correlate with the outcomes it values. But he said the measures must be used carefully. More token use can raise costs, while a focus on lines of code can create unnecessary complexity.

He also recommended that managers pay particular attention to teams at both ends of the AI adoption spectrum: those in the bottom 10%, to understand why they are not using AI effectively, and those in the top 10%, to determine whether heavier use is translating into faster delivery.

Terkowitz said Amazon's most AI-forward "frontier teams" have shown stronger productivity and delivery. He also said teams and individuals that are not adopting AI or increasing output metrics are falling behind.

But his memo left room for engineers whose work may not yet benefit from current AI tools. In those cases, he said, employees should document why and work toward a solution by sharing their findings with peers and managers.

"An engineer who can explain where AI does not yet help their work is demonstrating the judgement we are asking for," the memo said.

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• Amazon launched a series of new devices this month, including Alexa tablets and Bee AI wearables.
• Rising memory costs forced "difficult trade-offs" on Amazon's device prices, sales, and profit.
• Amazon is seeking more Alexa revenue from enterprise sales, licensing, and ads.

Amazon launched a flurry of new consumer devices this month. Behind the scenes, rising memory costs are adding pressure to its already money-losing hardware business.

An internal planning document obtained by Business Insider shows Amazon forecasting a $612 million gross loss this year for its first-party devices business, compared with a leadership target of a $438 million loss.

The document said rising memory costs were "putting pressure" on the business's profitability, forcing "difficult trade-offs" among sales volumes, average selling prices, and gross profit.

The projected $612 million loss was at the gross profit level, meaning it did not account for all operating expenses, such as R&D, sales and marketing, and administrative costs.

The figures offer a rare glimpse into the pressure on Amazon's hardware business as it absorbs rising component costs. Other tech hardware companies, including industry leader Apple, face similar pressure from surging memory chip prices.

An Amazon spokesperson declined to comment.

A new wave of AI devices

Despite the pressure, Amazon continues to expand its consumer hardware lineup. Even if the company loses money on device sales, it can make money in other ways, such as subscription services, as more customers use its gadgets.

In October alone, the company introduced new Kindles, Alexa-powered tablets, Ring smart locks, and AI wearables under its Bee brand. The August planning document identified Bee and new smart glasses as strategic products still in an investment phase.

Amazon has historically used low-cost hardware to pull customers into a broader ecosystem of shopping and digital content. Rising component costs could make that strategy more expensive, forcing the company to raise prices.

The clearest shift is in Amazon's tablets. Earlier this month, the company phased out Fire tablets after 15 years and replaced the budget-friendly lineup with pricier Alexa Tablets powered by Alexa+. The new devices cost between $229.99 and $499.99, a notable increase from previous generations.

Not just Amazon

The planning document was prepared in August, the same month Amazon raised prices on products including Echo speakers, Kindle e-readers, and Fire TV devices.

The pressure extends beyond Amazon. Apple has raised prices on some Macs and iPads, while Microsoft and Sony have increased console prices. Dell, HP, and Lenovo also face higher memory costs.

The AI boom is helping drive the squeeze. Huge data center investments have increased demand for memory chips, while manufacturers have devoted more capacity to high-bandwidth memory used in AI servers. That has tightened supplies and raised prices for components used across consumer electronics.

Amazon is experiencing both sides of the boom. It expects roughly $220 billion in capital expenditures this year, largely to expand AWS data centers for AI demand, while higher component costs squeeze its consumer hardware business.

The rising cost of Alexa+

The August planning materials show Amazon reassessing both Alexa+ revenue and operating costs. They called for updated forecasts, expansion through enterprise sales and advertising, and more detailed AWS cost modeling.

Amazon is now confronting the cost of operating Alexa+ at scale. Business Insider reported in July that internal forecasts put Alexa+'s AWS cloud costs at roughly $1.7 billion in 2026, nearly triple the prior year's figure. Amazon was working to lower those costs by relying less on Anthropic's AI models and routing more requests to its own, cheaper systems.

A separate project called Moonraker, intended to give Alexa more advanced AI-agent capabilities, was projected to require more than $100 million in GPU spending this year. Amazon internally considered delaying or scaling back the initiative as one option for easing cost pressure, Business Insider previously reported.

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