Amazon is stepping up its push to make AI central to its engineering culture.
As part of that effort, its massive retail business, known as "Stores," has formalized how teams build with AI, distilling its approach into a set of internal "AI-native engineering tenets," according to an internal document obtained by Business Insider.
The internal guidelines outline a pragmatic playbook. Rather than forcing AI into every use case or adopting every new model, Amazon emphasizes balancing speed, cost, and control, with clear expectations around transparency.
The tenets are central to Amazon's broader "AI-native" strategy, aimed at scaling usage across thousands of teams and closely tracking adoption, as Business Insider previously reported.
"Amazon's Stores engineering teams found that integrating AI across the full development lifecycle — not just bolting it on as an afterthought — delivers the most meaningful gains in what we're able to invent for customers and how quickly we can deliver it," Montana MacLachlan, an Amazon spokesperson, told Business Insider.
"We've also identified opportunities for improvement, and those results, along with our proven approach to AI adoption, informed the ambitious goals we've set for some Stores engineering teams in 2026," she added.
Here are the 6 tenets:
- Delivery first, cost second: We prioritize working, effective solutions over cheap ones. This means we will build now, then optimize for compute cost later.
- AI-native is not AI-exclusive: We will use the best approach to solve the problem we face. Sometimes that will require AI, and sometimes the AI will be an LLM, but not always.
- Cutting edge, not bleeding edge: We will not try to keep pace with AI technology. We will evaluate and retain flexibility to switch if the benefits outweigh the costs; sometimes foregoing the newest improvements.
- With you, not for you: We will rely on existing teams' expertise and will not become domain experts in your area. Participating in our pilots requires bringing your domain expertise and time investment.
- Not all preferences are requirements: Although we will aim to delight our customers, we will not accommodate all their preferences. Instead, we will optimize for hundreds of teams, not just a few.
- No black boxes: All the solutions we deploy must be auditable, understandable, and traceable. We will forego performance and cost improvements to maintain human understanding and traceability.
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