AI-native software development requires a new engineering model
Artificial intelligence has quickly become a standard part of modern software development. Coding assistants, code completion tools and AI-powered integrated development environments are now widely available, yet many engineering organizations continue to struggle with the same fundamental challenge: developer productivity.
Approximately 65% of organizations report that engineering teams spend just 0–20% of their time on net-new innovation. The majority of developer capacity is still consumed by maintenance, migrations, reviews, operational toil and context switching. The problem is no longer access to AI tools but how organizations redesign AI-native software development around them.
In the latest episode of the AppDevANGLE podcast, Deepak Singh, vice president of developer agents and experiences at Amazon Web Services Inc., and Steve Tarcza, director of software development at Amazon, joined me to discuss why the next generation of software development is shifting from AI-assisted coding to AI-native engineering workflows.
AI productivity isn’t a tooling problem
