Qualify: Understanding Agent Identity and Know Your Agent (KYA) Protocols What Is Agent Identity in AI-driven Financial Systems? Agent identity refers to the unique, verifiable digital persona of an autonomous agent—such as an AI-powered software application or bot—that acts on behalf of a user or organization within financial
Defining the Problem: Reliability Challenges in AI Agent Execution on Web Platforms The rapid evolution of autonomous AI agents is transforming how organizations approach digital workflows and business operations. Yet, as enterprises rush to harness these advancements, a critical issue looms large: today’s web platforms are fundamentally ill-equipped to
Qualifying Agentic AI: Defining the New Era of Business Automation The business world is undergoing a profound transformation as we enter 2026, with Agentic AI at the forefront of this change. As organizations strive for greater agility and innovation, understanding what sets Agentic AI apart—and why it matters—is
Overview of System of Action and Intent-to-Execution Compression As AI reshapes global enterprises, the System of Action has emerged as a transformative paradigm that bridges human intent and machine execution at unprecedented speed. This foundational concept lies at the heart of modern agentic AI architectures, driving operational agility by collapsing
The Challenges AI Agents Face on Today’s Web Infrastructure AI agents—autonomous software systems capable of planning and executing multi-step actions while making real-time decisions—are advancing faster than the web infrastructure they rely on. Over the past few years, agent-based systems have moved beyond demos and internal experiments
Why the Web Still Struggles With AI Agents Conversations about AI agents tend to accelerate very quickly. Almost too quickly to notice what gets left behind. The early part is always the same. People talk about capability. About how far autonomy can go. About how many steps an agent can
Insights The Quiet Side-Channel This isn't a continuation. Not really. Most of what I’ve written before follows a certain trajectory, a push toward a finality that feels good on paper. But this piece refuses that. It’s a side chapter, a moment where the gears grind because
Notes from real environments where agents behave correctly and still fail There’s a specific point where AI agents stop feeling impressive and start feeling confusing. It usually happens after the demo phase, once the agent is connected to something real. Not a mocked endpoint or a sandbox, but an
What We Keep Seeing in the Real Web If you have spent any real time trying to run AI agents on live websites, some patterns start to repeat. At first, things look fine. The agent responds clearly. The plan feels reasonable. Early tests pass without much effort. Then the agent
Anyone who has tried to connect an AI agent to the real web has probably felt this gap. The model is capable. The reasoning makes sense. In isolation, everything works. But once the agent is wired into a live website, things start to unravel. Flows that worked yesterday suddenly fail.
It’s Not the Model — It’s the Execution Environment If you’ve ever tried to connect an AI agent to the real web, this probably feels familiar. The agent works fine in isolation. It reasons well, plans correctly, and produces sensible outputs in testing. But the moment you wire
The Agent Economy Has a Plumbing Problem: Why We Are Rebuilding the Web for AI Let’s be honest about the last thirty years of tech history. From the clunky desktops of the 90s to the sleek cloud architectures of today, every single line of code, every interface, and every