Deep dives on AI agent governance, MCP security, compliance, and enterprise agentic architecture.
Non-human identities (NHIs) like service accounts, API keys, and AI agents now outnumber people many times over. Learn what NHIs are, why they are a security risk, and how to manage and secure them.
LLM observability is how teams trace, monitor, and evaluate large language model apps in production. Learn the three pillars, key metrics, architecture, and best practices.
Shadow AI is the unsanctioned use of AI tools, agents, and MCP servers inside your org. Learn the real risks, examples, and how to detect and govern it.
AI security posture management (AISPM) helps you discover, inventory, and reduce risk across AI models, agents, and pipelines. Learn how AISPM works, how it compares to CSPM and DSPM, and how to start.
Learn what Playwright MCP is, how it works, and how to set it up. Covers architecture, features, use cases, CLI vs MCP, and best practices for AI browser automation.
Learn what MCP is, how it works, its architecture, key concepts like tools and resources, security risks, and how to get started building with it.
Learn how to implement MCP access control for AI agents with OAuth 2.1, RBAC, CBAC, and Zero Trust enforcement patterns for platform and security teams.
Learn what MCP tools are, how AI agents discover and invoke them, top MCP servers to use, and how to build, secure, and deploy your own MCP tools.