Everything is changing, and Scrum is changing too. I don't want to give the impression that this post is a prediction. I don't know what the future will look like, and nobody does, including the CEOs of the hyperscalers.

But this is how my teams have been working over the last few years. Our workflow hasn't changed, but our roles are changing.

Spec → Plan → Task → Test → Review → Commit

More precisely, we are learning a new kind of rhetoric. Why? Between every step there's an agent doing some of the work.

What surprised me is that the agent didn't make the process less important. I think the engineering approach stays fully in place, even when we use AI. When you give an agent a vague story, you get a vague result. When you give it a small task with clear acceptance criteria, it does a very good job. So we are discovering a new rhetoric for working with AI.

A good task for an AI agent is:

• ✔ small (minutes to hours, not days)
• ✔ testable (Given / When / Then)
• ✔ traceable (task ID in the commit)
• ✔ and last but not least, reviewed by a person

This is the new reality with LLMs, at least for now, at least at daenet/ACP.

The value isn't in the model. It's in us: in how well we specify, split and verify the work. The engineering discipline we have always taught is suddenly worth more, not less.

I'd be happy to hear your suggestions and thoughts.

AI #AgenticAI #Scrum #SoftwareEngineering #daenet

Originally published on LinkedIn.