On 27 October 2026 Amazon published a memo from Terk Terkowitz, VP and Distinguished Engineer at Worldwide Amazon Stores, describing a revised role guideline for its software development engineers (SDEs). The memo says AI is changing software engineering "both more quickly and more fundamentally" than earlier shifts such as cloud and microservices, and that Amazon will measure engineers on outcomes instead of tool usage.
What the memo says
Amazon's SDE guidelines have historically avoided naming technologies. This time the Senior Principal and Distinguished Engineer communities debated whether AI is different, and concluded that it is. The memo tells engineers to learn and apply AI in daily work, and states that AI will be at the centre of software engineering practice.
The guideline does not define what good AI practice looks like. Amazon's reasoning is that any definition written now "will likely look antiquated by this time next year". It focuses on what stays constant: impact on customers, on the business and on teams.
The memo is also open about measurement. Amazon prefers to judge engineers on long-term outcomes, which it describes as time delayed and hard to isolate. Where it has used input metrics such as token usage or AI tool adoption, or throughput metrics such as code changes and reviews, it calls them flawed proxies. It also says that finding where AI falls short is "a finding, not a failing".
Two further points stand out. Amazon says engineers who stay close to their products and customers get the most from AI, and it wants to reverse a trend of some engineers becoming less connected to the business. It also says its approach can serve as a model for its customers.
What it means for engineering teams
The memo supports a pattern seen in this year's surveys: usage is easy to count and outcomes are not. If your team tracks prompts, accepted suggestions or lines of code, Amazon's own reading is that those numbers describe activity. Cycle time, review time, defect rates and customer results are slower to collect and closer to what the business cares about.
It also shifts what the job description asks for. Amazon expects AI use from every SDE and then evaluates the judgement applied on top of it: knowing the customer, owning the result and deciding when AI output is not good enough.
What it means when you hire engineers
A large employer that expects daily AI use and measures outcomes sets a reference point for what a senior engineer looks like in 2026. A candidate who lists tools tells you little. A candidate who can describe a product result they owned, and where AI output fell short and what they did about it, gives you the evidence the memo points to.
That shapes interviews as well. Testing someone with AI tools on and off, in a real codebase, shows both their own skill and how they direct and check an agent. Miyagami's engineers are each tested by an AI-native tech lead who works with AI every day, and you can read how that works on how we vet. If you are weighing a senior hire against that standard, AI-native engineers describes the profile.
The memo is one company's guideline for its own staff and does not report measured productivity results. It shows how a large engineering organisation now frames the role, and it gives engineering leaders a published position to compare their own expectations against.
Sources
