Shipping faster usually fails for one simple reason: teams try to increase release velocity by taking on more risk. Progressive delivery acts as a technical bridge that allows high-performing teams to decouple deployment from release, which enables speed and experimentation with less harm and a whole lot more user feedback.

The 2025 DORA report found that AI tends to increase pull request (PR) size by 154%, expanding the blast radius of any release. Breaking work into small, manageable chunks reduces that risk, while progressive delivery practices can reduce your blast radius. Both are essential to manage deployments when unpredictable AI elements are involved.

In this panel, hear how high-performing teams are actively following platform engineering best practices, reducing blast radius, and turning every rollout into a learning loop.

Join the panel and learn:

• How to increase deployment frequency without increasing risk with progressive delivery
• How to build an experimentation rhythm so teams can validate ideas with user behavior
• How to shift from “big-bang” releases to lower-risk, smaller daytime releases