Frontier teams are not just using AI to code faster. They’re redesigning how software gets built. The result is 4.5x productivity gains, in some cases more than 10x.
Six engineers. Seventy-six days. A project scoped for 30 developers over 12 to 18 months, delivered within a quarter. That is not hypothetical. It’s what happened when an Amazon Bedrock team stopped treating AI as a coding shortcut and started treating it as the foundation of how they work. The team shipped more production code in five months than in the previous ten years.
The gap between teams like this and everyone else is widening fast. AI coding agents have fundamentally changed the rate at which software gets written, but not the rate at which it reaches customers. Commits are surging, and CI/CD pipelines are busier than ever. Yet, features shipped to production have not kept the same pace. The bottleneck is not the agent’s ability to generate output. It is the agent’s access to the knowledge it needs to make good decisions, and the team’s willingness to restructure work around that reality.
We call the teams that have figured this out “frontier teams.” They are not confined to elite labs. They exist across industries and company sizes, and they share a common discipline: they treat AI adoption as an engineering investment, not a tool rollout. Any engineering team can become a frontier team; we can show you how to get there.
