AI is writing your code. But who's governing it?

Software teams are shipping faster than ever — and faster than most organizations can trace, govern, or trust. The debt accumulates quietly: in rework, in triage, in risk that only surfaces when it's expensive.

We've been sitting with one question: What would it actually take for agentic AI to be fast AND accurate at enterprise scale?

The answer is context. The more your agents understand — your codebase, your workflows, your constraints — the less you clean up later.

Join us on June 10th at GitLab Transcend, Livestreamed globally where we share what we've built, what we've learned, and where we're going next.

Agenda:

1. Platform innovations across the full software lifecycle — making your AI agents faster, smarter, and more cost-effective.
2. New research from Stanford's SWEPR team — fresh data on software engineering productivity in the AI era.
3. Enterprise voices you'll want to hear from — Mercedes-Benz on running vehicle software at scale. Google Cloud on what governed enterprise AI actually looks like in practice. Compare the Market, Cube, and AWS on the future of software engineering, with real-world results to back it up.
4. Industry survey data quantifying the gap between AI adoption and genuine engineering efficiency — because those two things aren't the same.

If you lead software engineering, development platforms, or AI strategy, this is where intelligent orchestration with context meets production reality.