Redefining Agile In The Age Of AI

Tim Lee is the Founder and CEO of Bookipi, an international SaaS company trusted by millions of small businesses worldwide.

For as long as I’ve built software, the rule has been the same: Deliver fast, fail fast. Get a minimum viable product (MVP) out the door, then gather user feedback to improve the next iteration. Agile took that instinct and turned it into a discipline, with shorter cycles, tighter feedback loops and quicker releases.

AI has changed that strategy, and not in the way most people expected. Product managers, designers and engineers can now spin up a working prototype in record time using code generators. When everyone can shorten development time with AI, being fast stops setting you apart. Research shows that AI can reduce the time developers spend on some development tasks—so those hours aren’t where the contest is won. Quality and user experience are.

That doesn’t make agile obsolete. What it means is that agile is shifting its center of gravity away from sprints, trouble tickets and ever-shorter release cycles and toward consistency of what ships.

Moving The Bottleneck Downstream

Agile was built for a different era—one when engineering was the scarcest resource in the building. Breaking work into small pieces and running it through scrums and sprints was how teams offset the sheer cost of human coding hours.

AI has knocked most of that cost out. Generating the first version of an application is easy now, and a machine can handle the working prototype, the tests and the documentation. The bottleneck now sits in human judgment, verification and integration. A 2025 randomized controlled trial by METR, a nonprofit research group, captured this sharply: Experienced developers using AI tools took 19% longer to finish their tasks, even though they believed the tools had made them faster. The speed was only real in feel, not in fact, because the effort simply relocated from writing code to reviewing, reconciling and validating what the machine produced.