Date & time
17:00
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AI coding tools made your team faster, but review processes weren’t built for that pace. The result is a lose/lose: either review becomes a bottleneck, or it gets rushed, and quality gaps slip through to production.
Drawing on Qodo’s analysis of its more than 50,000 issues uncovered daily, this workshop introduces a practical framework for AI code quality and governance that engineering leaders can act on immediately.
Traditional code review was never designed to be the quality gate for AI-velocity development. This workshop gives engineering leaders a practical path forward.
Through live polls, real-time self-assessments, and a live demo, you’ll leave with:
- A clear distinction between code review and code verification, and why it defines your risk exposure.
- A framework for embedding code quality and governance best practices across your engineering lifecycle.
- A phased rollout model for scaling code governance across distributed teams and repos, without sacrificing velocity.
If your team has adopted AI coding tools and is now feeling the pressure on quality and consistency that comes with faster output, this session was built for you.
