In the first few months of 2026, AI-attributed commits on public GitHub grew from under two million to an estimated 37 million per month. Writing code got cheap. Knowing whether a change actually worked didn’t. Staging environments, hand-written tests, and human review weren’t built for this volume.

In this session, Diamond and Mike show how Datadog validates every change from pull request to production with automated release agents, intelligent PR reviewers, and more. Learn how you can start to build a self-driving software factory of your own by leveraging these building blocks. 

Key Takeaways:

• Keep pace with AI-generated code without sacrificing quality. Learn why traditional testing, staging, and manual review processes are struggling to keep up with AI-driven development—and how to modernize software validation.

• Automate validation from pull request to production. Discover how Datadog's automated release agents, intelligent PR reviewers, and integrated observability help teams identify issues earlier, validate changes faster, and reduce manual intervention.

• Build the foundation for a self-driving software factory. Explore practical building blocks for creating a more autonomous software delivery process that accelerates releases while maintaining confidence in production reliability.