Here's the question keeping engineering leaders up at night: how do you scale delivery speed when your risk detection was built for a different era?

AI agents now write, deploy, and consume APIs on their own, at a pace existing governance was never designed to handle. The result: breaking changes slip through, compliance drifts, and coverage gaps open up in places your test suites don't even look.

Conventional CI/CD pipelines have blind spots, especially when APIs aren't built by a human. Closing them means governance that runs at the same velocity as the agents themselves: testing and policy enforcement that catches problems the moment an API is written, not after it ships.

Join Matthew Bonner, Solution Architect, and John Monahan, Solution Engineer at SmartBear, as they talk about how AI-native governance closes these gaps at agent speed.

Who should attend:

• Engineering and platform leaders responsible for API quality, security, or compliance


• Anyone whose teams are using AI coding assistants or agents to generate, modify, or deploy APIs


• QA leads who need CI/CD governance to keep pace with agent-driven development


• Technical decision-makers evaluating how to scale AI adoption without losing control over risk

What you'll take away:

• Where existing CI/CD pipelines still have blind spots in agent-driven development


• The specific risks AI-accelerated changes introduce that current tooling misses


• How agent-based governance closes the gap without slowing your teams down