IT之家 (ITHome) news, October 28: On the 27th local time, Amazon updated its software engineer job guidelines for the AI era, emphasizing that evaluations should be based on how much business value engineers create, rather than how much AI they use.how much business value they have creatednot how much AI they have used.
Amazon Vice President and Distinguished Engineer Turk Turkovic pointed out that, compared with previous technology shifts like cloud computing, AI's impact on software development has come faster and more profoundly. Still, the key to measuring engineer performance remains what outcomes they deliver for customers and the business, not how often or how much they use AI. "We all have to adapt to change and take time to learn, or we risk being left behind."
AI coding tools and agents are transforming the software industry, and programmers' work is changing along with them. Amazon calls this stage the "Renaissance Developer Era", believing that combining human judgment with machine intelligence can lead to faster, more efficient development of new products and services.
The software industry is undergoing transformation, and the professional role of software engineers is changing as well. In recent years, Amazon has paid increasing attention to engineers' and technical managers' AI usage and has tried to incorporate it into evaluations. The company has tracked employees'number of AI uses, tokens consumed, and lines of code written, and even created leaderboards based on some of these metrics to compare different teams.
However, the memo warns that using these data to measure job performance is one thing, while requiring employees to maximize the numbers is another.Overly pursuing metrics can backfire—for example, abusing AI just to increase token consumption without writing better software or improving the customer experience. Turkovic said: "If these metrics are treated as goals rather than references for measuring work,it may produce negative results."。”
According to Business Insider, Amazon had previously tried different approaches, hoping both to measure engineering teams' AI usage and to encourage employees to use AI more.
Earlier this year, Amazon began tracking engineers' use of internal AI tools, and some teams launched leaderboardsbased on data such as token consumption. This sparked dissatisfaction among some employees, who worried that adding unnecessary actions to meet AI usage requirements could earn recognition more easily than genuinely improving work efficiency.
The new guidelines represent Amazon's clearest public acknowledgment to date, showing that the companyis aware of this risk. Amazon believes that detailed rules on how engineers should use AI could quickly become outdated due to technological progress, so the new guidelines focus onlong-term outcomes for customers and the business.
IT之家 has learned that Amazon has not reduced its emphasis on AI adoption because of this. The company stressed that AI should become "core to software engineering practice" and requires engineers to use the technology in their daily work.
The memo also requires managers topersonally use AI tools in actual projectsto understand what problems AI can solve and where it still falls short, and to explain the basis of their judgments to their teams.
Turkovic noted that Amazon has found that data such as token consumption, AI tool usage, and code reviews do have some correlation with the work outcomes the company values, but one cannot look only at the numbers. Consuming more tokens means costs may rise, and blindly pursuing lines of code can also make software unnecessarily complex.
For teams with widely varying AI adoption, managers need to closely examine two groups: the bottom 10% of teams, to understand why theyhave failed to use AI effectively; and the top 10% of teams, to confirm whetherheavy use of AI has actually accelerated work delivery。
. Amazon found that its most enthusiastic AI users, the "frontier teams," achieved better results in productivity and delivery performance. Conversely, teams and employees that did not adopt AI, or failed to improve output metrics, gradually fell behind everyone else.
However, the new guidelines do not mean that all engineers must prove AI boosts their productivity. For roles that cannot yet benefit from existing AI tools, employees may document the specific reasons and discuss them with colleagues and managers to jointly find solutions. The memo states: "Engineers who can explain why AI is not currently helping them are demonstrating exactly the kind of judgment we want to see."