Amazon tells its engineers to avoid the ‘bleeding edge’ in new 6-point AI adoption guidelines

Amazon is formalising how it builds with artificial intelligence as part of a broader push to make AI central to its engineering culture, according to a report by Business Insider. Reportedly, the tech giant’s massive retail division, known internally as “Stores”, has formalised its approach into a set of six “AI-native engineering tenets” designed to guide how teams should approach AI development across the organisation.

The report notes that the internal guidelines are modelled as a realistic playbook instead of forcing AI models into every possible use case. The new strategy is said to emphasise balancing speed, cost and control, with clear expectations around transparency.

The six tenets are also said to be central to Amazon’s broader ‘AI Native’ strategy, which looks to scale AI usage across thousands of teams internally while closely tracking adoption.

Montana MacLachlan, an Amazon spokesperson, told Business Insider on the policy, “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.”

What are Amazon’s six AI rules?

Delivery first, cost second:

In a notable directive for a company famously focused on frugality, Amazon is prioritising working, effective solutions immediately.

“We prioritise working, effective solutions over cheap ones. This means we will build now, then optimise for compute cost later,” the policy reads.

AI-native is not AI-exclusive:

Amazon is instructing its engineers to use the absolute best approach for the problem at hand, whether it involves using an LLM or not.

“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,” Amazon’s directive reads.

Cutting edge, not bleeding edge:

Amazon is also actively warning engineers against constantly adopting the latest AI advancements and instead focusing on practical, stable technologies while remaining flexible enough to switch when needed.

“We will evaluate and retain flexibility to switch if the benefits outweigh the costs, sometimes foregoing the newest improvements,” the policy reads.

With you, not for you:

Amazon is asking its AI teams to work alongside domain experts rather than replace them, relying on existing team knowledge to guide implementation.

“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,” reads the policy.

Not all preferences are requirements:

Amazon’s policy notes that not every customer preference needs to be accommodated. Instead, Amazon wants to build systems that work effectively at scale across hundreds of teams.

“Although we will aim to delight our customers, we will not accommodate all their preferences,” reads the policy.

No black boxes:

In what is arguably the most critical tenet for enterprise safety, Amazon mandates that all deployed solutions remain auditable, understandable, and traceable.

“We will forego performance and cost improvements to maintain human understanding and traceability,” reads the policy.