The Code Governance Layer Your AI Stack Is Missing

August 25th at 1pm ET

AI has given engineering teams velocity. Now, enterprise teams face a question the current AI stack does not fully answer: how do you know the AI-generated code is ready to ship? Most enterprise teams don’t, and the data show the cost. Incidents per PR are up 242%.   

Scaling agentic development requires more than LLM prompts.  It takes a system: checks, standards, and accountability applied to every code change. That system has to verify code independently, enforce your organization’s requirements, and show engineering leaders whether quality is holding as agents take on more of the work. This is the governance layer most AI stacks are missing.

Join Qodo CEO and co-founder Itamar Friedman as he breaks down what that layer looks like and why AI code quality and governance are becoming the defining challenges of the agentic era. You’ll leave with a framework for managing the risks of agent-written code and putting AI to work across your teams without sacrificing speed, security, or control.

What You’ll Learn:

• Why the old quality model broke: How AI velocity outran the review process, and how to manage the new bottleneck in AI Code Review. 
• What leaders can’t currently see: Why most organizations have no view into whether standards are followed, and the visibility that a system of record for code quality provides.
• From tribal knowledge to enforced standards: How the standards in your reviewers’ heads and PR history become machine-readable rules, enforced consistently across every team, repo, and AI tool.
• Quality as a per-system measure, not per-repo: Why the costliest failures cross repository boundaries, and how cross-repo reasoning catches breaking changes before merge, not in production.
• Governing the AI tooling you can’t see: How to bring the skills and agent workflows already shaping your code under central visibility, control, and measurement.