Uploaded May 2026 | Updated September 2026, 2 weeks ago
AI coding tools have dramatically increased developer velocity, but they haven't eliminated the need for code review. In fact, they've made it more critical than ever.
In this session, Erik Thorelli, Developer Experience Lead at CodeRabbit, shares how engineering organizations can operationalize AI-driven code review as a scalable, production-grade quality gate. Drawing from real-world deployments across thousands of teams, he will walk through the systems and practices required to manage AI-generated code safely and effectively.
Attendees learned how to move beyond prompt engineering into context-rich review systems, implement secure and isolated verification workflows, and build feedback loops that continuously improve model performance. The session also covered model lifecycle management, observability, and how to measure ROI through meaningful engineering outcomes. Designed for engineering leaders, AI operators, and senior developers, this talk provided a practical blueprint for deploying AI code review in environments where reliability, security, and scale are non-negotiable.
AI coding tools have dramatically increased developer velocity, but they haven't eliminated the need for code review. In fact, they've made it more critical than ever.
In this session, Erik Thorelli, Developer Experience Lead at CodeRabbit, shares how engineering organizations can operationalize AI-driven code review as a scalable, production-grade quality gate. Drawing from real-world deployments across thousands of teams, he will walk through the systems and practices required to manage AI-generated code safely and effectively.
Attendees learned how to move beyond prompt engineering into context-rich review systems, implement secure and isolated verification workflows, and build feedback loops that continuously improve model performance. The session also covered model lifecycle management, observability, and how to measure ROI through meaningful engineering outcomes. Designed for engineering leaders, AI operators, and senior developers, this talk provided a practical blueprint for deploying AI code review in environments where reliability, security, and scale are non-negotiable.
