AI can now produce code faster than teams can decide what should be built—or what “Done” means. When code becomes abundant, the bottleneck moves.

​

Meet InternGPT: PhD-level capability, third-day judgment, and enough free time to open eleven pull requests before lunch.

​

In this session, Nate Adams explores what happens when AI joins the software development team and begins amplifying both our strengths and our dysfunctions.

​

You’ll explore:

• Where the bottleneck moves when code generation is no longer the constraint.

• How AI changes refinement, development, testing, and peer review.

• How acceptance scenarios can guide development, testing, and review.

• What belongs in the Definition of Done when AI agents perform some of the work.

• How to give AI agents bounded autonomy without surrendering accountability.

• Practical ways to create smaller changes, stronger feedback loops, and less review overload.

 

Drawing on experiments underway at Lee Enterprises, Nate will show why Scrum fundamentals—clear outcomes, small increments, meaningful inspection, and fast feedback—become more important, not less, when AI accelerates delivery.

 

The goal isn't to out-type the robot. It's to redesign the system around it.