CTO AI Corner: Scrum feels out of place in AI enhanced software development

Lately, I’ve had several conversations about development frameworks, especially in greenfield projects. The impact of AI tools is significant enough that our ways of working need to evolve too. Scrum, in particular, seems to have some trouble keeping up, so here are a few thoughts for discussion.

Are 1 to 4 week sprints still useful? Sprint planning assumes some predictability, but now we often discover a better way mid-sprint or even complete more tasks than expected. Maybe we need shorter sprints. Or maybe no sprints at all. A continuously evolving backlog with real-time prioritization might serve us better.

Product Owners need to step up. It's no longer enough to drop by for a review. With AI accelerating prototyping, especially in UI/UX, the PO should be embedded in the team’s daily rhythm. Quick, real-time reviews can replace weeks of iteration loops.

Estimating tasks even on a planning poker level has become a guessing game. I used to be decent at it. Not so much anymore. Even the vibe coding experts can't predict how long something will take with AI in the mix. The tooling is evolving too fast. Spending time estimating is starting to feel like a ritual with no real value.

Also, team size. I mentioned this in an earlier post, but it’s worth repeating: large teams working in the same codebase just doesn’t work anymore. Smaller is faster.

Here’s what has worked for us:

  • Kanban-style continuous planning and prioritization
  • Daily availability of the PO for rapid “AI-storming” sessions
  • Demo sessions at least twice a week
  • Very rough task sizes: small or large
  • Two-person teams
June 18, 2025
Authors
Tomi Leppälahti
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