Deep dives on AI agent governance, MCP security, compliance, and enterprise agentic architecture.
The OWASP Top 10 for LLM Applications (2025), risk by risk: what LLM01 to LLM10 cover, real attack examples, mitigations, and MITRE ATLAS mappings.
Prompt injection is the top security risk for LLMs and AI agents. See how direct and indirect attacks work and get a defense-in-depth playbook to stop them.
An MCP platform is the governance layer above your MCP servers: identity, access, policy, observability. See how it differs from a gateway and how to pick one.
AI risk management is how enterprises identify, assess, and control AI and agent risk. Compare NIST AI RMF and ISO 42001 and build a program that scales.
The NIST AI Risk Management Framework is voluntary guidance for governing AI risk. Learn its four functions, the GenAI Profile, and how to put it into practice.
AI governance sets the policies and controls for safe, compliant AI. Learn the pillars, NIST, ISO 42001, and EU AI Act frameworks, and how to govern AI agents.
AI observability is how teams see and govern LLM and AI agent behavior in production. Learn the core pillars, key metrics, and how to catch failures early.
What an enterprise AI platform is, its reference architecture, how to evaluate build vs buy, and how to secure and govern autonomous AI agents.