Topic hub
Agentic systems in the enterprise: the Model Context Protocol, single- versus multi-agent design, and what ships reliably.
Start with the pillar guide
Agentic AI is the shift from AI that answers to AI that does. What an AI agent actually is, where they deliver value, how they work under the hood, the single-vs-multi-agent decision, and how to build them without joining the projects that fail.
Read the guideAgents rarely fail because the model is weak. They fail because the engineering that makes them observable, measurable, and reliable isn't there. Why agents break in production, and the discipline that fixes it.
The agent framework landscape shifted more in early 2026 than in all of 2025. Which frameworks matter for production, how to choose by workload, when you don't need one, and the thing every framework leaves out.
An AI agent that can't reach your tools is just a clever conversationalist. MCP is the open standard that changed that. What MCP is, the integration problem it solves, how it works, why it matters, and the security caveats.
Multi-agent systems get treated as the sophisticated upgrade. The evidence says otherwise. What single vs multi-agent actually costs, when each wins, the patterns that survive production, and how to decide.
