From Coding Capacity To Decision Velocity: Five Principles For The Agentic Software Development Life Cycle

Software development is on the cusp of a true paradigm shift. The rise of agentic tools that handle significant portions of coding and delivery work is driving a fundamental change in how software is built, governed, and scaled. Development teams will require fewer people, and the work of those people is all the more critical as the shift to an AI-native model enables organizations to automate key steps in the software development lifecycle (SDLC). People provide oversight and quality assurance; human judgment ensures that what’s produced is trustworthy and delivers real customer value.

For decades, people have defined and developed software. Agile built a human-centric model around the 8 to 12-person squad. In a typical team, most effort went into Build (approximately 32% percent, per AlixPartners’ Activity Reference Model) and Test (approximately 18%), with only about 7% devoted to Guide — the work of identifying problems worth solving. Automation helped through build pipelines,