Product security in an AI world

Practical guidance and best practices for product security teams now that AI writes code, reviews it, and probes it for weaknesses.

What the guide covers

Finding vulnerabilities

Using AI agents and scanners to find security bugs, and deciding which results are real.

Context for review

Giving models the code, architecture and history they need to review changes well.

Prioritizing risk

Mapping where risk concentrates across a codebase so effort goes where it matters.

Remediation

Fixing what you find with AI help, and measuring whether the fixes hold.