Most developer security training is generic, manually assigned, and disconnected from real development activity. Developers often repeat the same vulnerability patterns because learning is not tied to the risks they actually create.

Adaptive Learning closes that gap by automatically delivering relevant learning based on real vulnerability data and AI-assisted development behavior.

Traditional security training is typically generic, static, and assigned manually. Adaptive Learning automatically aligns learning to real developer activity and actual software risk.

Instead of assigning broad catalogs of content, Adaptive Learning delivers focused learning tied to:

• Real vulnerabilities
• Active repositories
• AI-assisted development activity
• Individual developer behavior

This helps organizations reduce recurring vulnerabilities instead of simply tracking training completion.

Adaptive Learning helps reduce vulnerabilities by identifying recurring risk patterns and assigning targeted learning before insecure behaviors become repeated development habits.

By connecting vulnerability findings directly to developer improvement, organizations can reduce recurring vulnerabilities at the source instead of relying only on downstream remediation.

Trust Agent: AI provides visibility into AI-assisted development activity. Adaptive Learning builds on that foundation by connecting AI-generated code risk and developer behavior to targeted learning.

Together, they help organizations move from AI visibility and governance to measurable risk reduction and developer improvement.

Adaptive Learning currently supports integrations with:

• Snyk
• GitHub Advanced Security
• Aikido
• Fortify
• Polaris

Support levels vary by integration and deployment mode.

Yes. Administrators remain in control of the content, structure, timing, and settings through Secure Code Warrior Quests. Adaptive Learning determines who receives training based on risk signals, while admins define the learning experience itself.

Yes. Adaptive Learning automatically identifies which developers should receive learning assignments based on real developer activity, AI usage, vulnerability data, and repository contribution patterns. This removes the manual overhead traditionally required to manage large-scale developer security learning programs.