Amazon Redefines Software Engineering for the AI-First Era
SEATTLE, WA – Amazon is fundamentally reshaping its software engineering practices to adapt to an era where artificial intelligence increasingly writes code. The tech giant has issued revised internal guidelines for its
SEATTLE, WA – Amazon is fundamentally reshaping its software engineering practices to adapt to an era where artificial intelligence increasingly writes code. The tech giant has issued revised internal guidelines for its vast developer workforce, shifting the emphasis from measuring AI tool usage to prioritizing tangible customer outcomes and business value.
This strategic pivot comes as Amazon grapples with the transformative impact of AI on its operations, even as it navigates past challenges with AI adoption. The company is also fostering new, agile development models, exemplified by a previously unannounced team within Amazon Web Services (AWS) called Velocity Labs.
A New Playbook for Engineers
The updated guidelines, circulated to engineers earlier this year, mark a significant departure from traditional performance metrics. Marc Brooker, an AWS vice president and distinguished engineer who helped author an accompanying letter, explained in an interview that the revisions steer away from metrics like “how many tokens are you spending, how many lines of code are you committing” because they don't necessarily equate to customer value.
Brooker emphasized that AI tool usage is not a direct factor in performance reviews or promotions, but rather its effective application to enhance performance. The new guidance encourages engineers to maintain a close connection to their customers and products, addressing concerns that some had become detached as the company grew.
Rapid Innovation with Velocity Labs
Adding to Amazon's evolving engineering landscape is Velocity Labs, a compact, 35-person team, primarily based in Seattle, launched in April. This group is designed to move at an accelerated pace, focusing on quick prototyping and exploration of underexplored AI areas critical to customers. Their mandate is to "move faster, explore more, and make sure AWS is at the cutting edge of innovation in agentic AI," according to job listings.
Velocity Labs recently demonstrated its agility by taking an open-source AI model, Strands Decider 2B, from concept to public release in under a week. This model, intended for quick decision-making within AI agents, was built by Brooker initially on his home GPU, with almost every line of code generated by an AI agent.
The Changing Role of Software Development
The impact of AI on daily engineering tasks is profound. Brooker noted that just two years ago, most Amazon developers manually wrote their code. Today, he asserts, "for the vast majority of our developer population, almost all of their implementation code is agent generated rather than human written." This represents a "massive change" in how software engineers approach their work, shifting from traditional code editors to AI agent tools like Kiro, Kiro Crew, and Anthropic’s Claude Code.
However, this transition hasn't been without its hurdles. Amazon previously faced scrutiny for shutting down an internal leaderboard, KiroRank, which ranked employees by their use of the Kiro AI coding tool, after discovering engineers were overusing it merely to improve their scores. The company has also acknowledged instances where inaccurate AI advice contributed to retail site outages, prompting the implementation of safeguards like mandatory peer review for AI-assisted changes in production environments.
Crucially, the new guidelines also offer flexibility, stating, "If your work does not benefit from current AI tooling, that is a finding, not a failing. Document why, share it with your community of peers, bring it to your manager, and work to find solutions." This empowers engineers to exercise judgment rather than blindly adopting AI.
Workforce Implications and Future Outlook
Amazon's shift comes amidst a period of corporate workforce adjustments, with roughly 30,000 corporate jobs cut since late 2025. CEO Andy Jassy anticipates AI will reduce the corporate headcount over time. Yet, AWS CEO Matt Garman indicated in April that Amazon is hiring "just as many software developers as we ever had," with thousands of interns and early-career engineers joining this year.
Brooker clarified that AI might not reduce the total number of engineers but will instead necessitate a different skillset. The company seeks engineers who demonstrate ownership, curiosity, and a capacity for rapid learning beyond their immediate expertise. He concluded that whether the solution is an advanced AI agent or simply "three lines of Python code, that’s great too,” emphasizing effective problem-solving over tool preference.
FAQ
Q: What is the main change in Amazon's software engineering guidelines? A: Amazon has revised its guidelines to focus on customer outcomes and business value rather than strictly measuring engineers' usage of AI tools or lines of code written. The goal is to encourage effective problem-solving, not just AI adoption for its own sake.
Q: What is Velocity Labs and what role does it play in Amazon's new strategy? A: Velocity Labs is a small, agile team within AWS (around 35 people) dedicated to rapid prototyping and exploration of new AI models. It exemplifies Amazon's push for faster innovation, having launched an open-source AI model, Strands Decider 2B, from concept to public release in less than a week.
Q: How is AI impacting the daily work of Amazon's software engineers? A: According to Marc Brooker, AI agents now generate almost all implementation code for the vast majority of Amazon's developers. This represents a significant shift in workflow, requiring engineers to transition from traditional coding to working extensively with AI agent tools. However, the company also acknowledges situations where AI might not be the best solution and encourages engineers to exercise judgment.
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