AI-assisted development can accelerate coding, but faster output does not automatically lead to better delivery. In this session, Nick Daniel and John Halberstadt examine how teams can use Agile ways of working to bring AI into the full delivery process, from understanding technical risk and shaping smaller, testable work to improving acceptance criteria, engineering practices, and feedback loops. They also discuss why human review, cross-functional collaboration, and gradual experimentation remain necessary as AI adoption grows. Watch the session for practical ideas on using AI to improve flow, quality, and learning without simply producing more software.
In this session, Jason Little shares a practical look at AI-assisted software development beyond the hype of “vibe coding.” Drawing from his own experience building a complex web application, he shows how Agile practices still matter when working wit…
