Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

My boss dropped a bombshell at 4:00 PM: build a secure, production-ready app from scratch by tomorrow morning. Instead of panicking, I put Claude Opus 4.6 to the test. In this video, I walk you through the entire end-to-end process of using an AI agent to architect, code, and debug a full-stack application. We’ll look at "Plan Mode," how the AI handles environment errors (like Windows SQLite issues), and most importantly, how we verified the AI's code for security vulnerabilities using Snyk.

As AI adoption grows, identity risk grows with it. Dirk Schrader, VP of Security Research at Netwrix, explains why governing human and machine identities is foundational to securing AI systems. How are you governing identity in your AI workflows today?

Securing LLM Workflows with Protegrity AI Developer Edition Learn how to protect sensitive data and prevent malicious prompt injections in your AI applications. In this technical walkthrough, Dan Johnson, Software Engineer at Protegrity, demonstrates a dual-gate security architecture designed to safeguard Large Language Models. Discover how to implement a security gateway that sits between your users and your LLM. This demonstration covers the integration of semantic guardrails and classification APIs to ensure data privacy and system integrity.

Want to test Protegrity’s data protection features without any local installation? In this tutorial, Dan Johnson shows you how to make your first protect and unprotect API calls directly in your browser using our interactive Jupyter Notebook (Binder). This is the fastest way to see Protegrity’s Python SDK in action—authenticating, applying protection policies, and maintaining data utility in real-time.

In this episode of This Week in NET, host João Tomé is joined by Emily Hancock, Cloudflare’s Chief Privacy Officer and Data Protection Officer, for a wide-ranging conversation about privacy in 2026 and how the role has evolved in the age of AI.