London

June 2–3, 2026

New York

September 15–16, 2026

Berlin

November 9–10, 2026

Derisking releases in the AI era

Learn the secrets of doing leading edge progressive delivery and experimentation in the real world.

Claire Knight, Ryan Vila, Jennifer Riggins and Liz Fong-Jones

Date & time

17:00

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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

panelists:

Ryan Vila

FME Domain Specialist
Harness

Claire Knight

Director of Engineering
n8n
Liz Fong-Jones

Liz Fong-Jones

Technical Fellow
Honeycomb

Moderator:

Jennifer Riggins

Freelance Tech Journalist