AI

With 88% of organizations now deploying AI agents in production, governance has shifted from a theoretical concern to an operational imperative. Yet 40% of technology executives admit their governance programs are insufficient. This article presents the technical infrastructure—the 'governance stack'—required to transform governance frameworks from policy documents into automated, enforceable reality across the entire agentic workforce lifecycle.

With 79% of companies already adopting AI agents, a critical governance gap has emerged. Without robust management frameworks, organizations risk a chaotic landscape of shadow AI, creating significant security vulnerabilities and operational inefficiencies. The solution lies in Private Agent and MCP Registries—command centers for agentic infrastructure that provide the visibility, governance, and security necessary to scale AI responsibly.

Anthropic has detailed its disruption of the first publicly reported cyber espionage campaign orchestrated by a sophisticated AI agent. The incident, attributed to state-sponsored group GTG-1002, signals that the age of autonomous, agentic AI threats is here. This post dissects the anatomy of the attack and explores how emerging standards like OpenID Connect for Agents (OIDC-A) provide a necessary path forward.

Anthropic has introduced two powerful but distinct approaches to AI customization: Claude Skills and the Model Context Protocol (MCP). While both aim to make AI more useful and integrated into our workflows, they operate on fundamentally different principles. This post explores their differences, synergies, and the exciting future they represent.

Attributing an LLM's behavior to 'non-determinism' is like blaming a complex system's emergent behavior on magic. It's an admission of incomprehension, not an explanation. The truth is far more fascinating and, for architects and engineers, far more critical to understand.

For decades, software architects have operated under a fundamental assumption: we design systems, and systems execute our designs. AI agents are rewriting this contract entirely. Unlike the monoliths and microservices that came before them, AI agents don't just execute architecture—they evolve it.

As AI agents become more sophisticated and autonomous, a fundamental question is emerging: should agents operate under user credentials, or do they need their own distinct identities? This isn't just a technical curiosity—it's a critical trust and security decision that will shape how we build reliable, accountable AI systems.

As AI assistants on platforms like Instagram, Facebook, and Booking.com become more autonomous, they need proper digital identities to securely act on our behalf. Learn how AI identity systems work and why they matter for consumer platforms.

Technical proposal for extending OpenID Connect Core 1.0 to provide a framework for representing, authenticating, and authorizing LLM-based agents within the OAuth 2.0 ecosystem.

Exploring the potential of AI agents in enterprise security and automation, and how they can enhance security operations.

Exploring the concept of a Minimum Viable Product (MVP) in AI applications, focusing on delivering value by understanding and addressing user needs effectively.