In many engineering teams, AI-generated code is creating a loop your current approach is not built to break. The same vulnerabilities show up in your codebase, scanners flag them, your team fixes them, and then they are reintroduced again. Code is moving faster, but the outcomes are not improving. Your team is stuck in repeat remediation, and the underlying problem is not getting solved.
The challenge is not a lack of tooling. Teams like yours already have scanners, training, and some form of AI guardrails in place. The issue is that these controls are static. They do not adapt to how your codebase evolves, and they do not learn from the issues your team is already fixing. As a result, vulnerabilities keep recurring, and your team continues to pay for them in review cycles, rework, and lost velocity.
In this session, we will break down why repeat vulnerabilities persist even in environments like yours and what it takes to actually reduce them at the source without disrupting how your team builds and ships code today.
In this webinar, you will learn:
