If you’re building AI agents in 2026, the hard part is rarely “the model.” The hard part isconnecting agents to tools and data in a way that’s reusable, governable, and production-safe.That’s exactly what Model Context Protocol (MCP) is designed to address. What is MCP? Model Context Protocol (MCP) is an open protocol that standardizes how … Read more
AI agents look magical in demos. In real operations, they’re more like a new employee who can click buttons across your systems — fast, confidently, and sometimes incorrectly. AgentOps is what makes agents safe to run in production: clear boundaries, predictable behavior, and the ability to explain what happened after the fact. The 3 levels … Read more
“SaaS is dead” is a dramatic headline. Traditional SaaS isn’t going away tomorrow. But the business model is under pressure, because AI agents are changing what buyers expect: not “give me a tool,” but “get the job done.” That shift is often described as Outcome-as-a-Service (OaAS): the vendor isn’t paid mainly for seats, features, or … Read more
Most “agent” articles still celebrate capability: a demo that can book a meeting or answer a ticket. In 2026, what leaders actually fund is operability: measurable outcomes plus the observability and governance to explain what the agent did, why it did it, and how to keep it safe at scale. Below are three fact-based case … Read more
AgentOps is the essential framework for teams moving beyond simple chatbots. A year ago, building a chatbot was progress. Today, it’s a liability if it’s not managed. Here’s a very Nordic moment: it’s Friday afternoon and a municipality rolls out an “AI assistant” to help staff answer procurement questions faster. On Monday, someone asks for … Read more