AI-driven development is no longer experimental, it’s embedded across the modern software development lifecycle. Coding assistants, LLM APIs, and autonomous agents now generate production code at unprecedented velocity.
But most organizations cannot clearly answer critical questions:
Which AI models generated specific commits
Where AI tools are influencing production code
Whether AI-assisted commits meet secure coding standards
How AI usage impacts overall software risk
Without visibility into AI-generated code, governance becomes difficult and accountability gaps emerge across the software supply chain. To scale AI development safely, organizations must be able to see, measure, and govern how AI contributes to software creation.
Join Secure Code Warrior’s Matias Madou, CTO, and Tamim Noorzad, Director of Product, to learn how AI Software Governance provides the visibility and insight needed to manage AI-assisted development at scale. You’ll also get an inside look at Trust Agent: AI, Secure Code Warrior’s governance layer designed to make AI tool usage, model activity, and commit-level risk visible across the development lifecycle.
You'll Learn:
How AI coding assistants and agents are expanding the software supply chain
Why visibility into AI-generated code is critical for governance
The key components of AI software governance; including developer capability and secure coding training
How organizations can measure software risk and strengthen secure development practices in the age of AI
