How do you build a secure engineering pipeline that natively produces compliant AI applications without slowing down agile development sprints?
In this clip from the Agentic AI Security Review at Swiss AI Weeks, Victoria Moroz and Fabio Sakita detail the 5-stage Trust Engineering Lifecycle—a structured process to design, build, and deploy autonomous AI securely.
The 5-Stage Lifecycle:
- Assess: Conducting threat modeling and risk gap analysis.
- Vision: Designing secure architectures, sandboxes, and human-in-the-loop thresholds.
- Build: Delivering compliant DevSecOps pipelines and API sidecar wrappers.
- Test: Executing agentic red teaming and rigorous stress testing engines.
- Operate: Running 24/7 AI Security Operations Center (AI SOC) monitoring.
Crucially, this cycle relies on continuous verification: every code commit automatically generates compliance artifacts, ensuring no unverified AI code ever hits production.
