Tag: MCP
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Internal AI Agents: Fix the Permissions First
Large companies are scaling internal AI agents first and the ones that work share one habit: they cleaned up permissions before the first connection, not after the first incident.
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Agentic AI MCP Server Governance: Vet the Server, Not the Call
What is agentic AI MCP server governance? Agentic AI MCP server governance is the set of controls that decides which MCP servers an agent may connect to, who decides that, and what a user can change. It works at the server level, not the tool-call level. So the question moves from “was this call safe?”…
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What Is Agentic AI Architecture? The Six Layers That Actually Decide Outcomes
Agentic AI architecture is the design of the system around the model: the layers that decide what an agent is asked to do, what it may reach, what it is forbidden to do, how far it may act without a person, and how any of that is proved afterwards. The model is a component in…
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27 Key Agentic AI Terms, What They Mean and Where They Came From
This is a glossary of 27 key agentic AI terms — what each one means, where it came from, and one authoritative source to read for each. The vocabulary of agentic AI has moved faster than any enterprise glossary I have seen in twenty years of consulting. Terms that were lab jargon eighteen months ago…
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Agentic AI Model Harness: The Layer That Decides Agent Outcomes
What Is an AI Model Harness? An AI model harness is everything wrapped around a raw language model that turns it into a working system — the system prompts, tool interfaces, context and memory management, the agent loop, orchestration, guardrails, permissions, sandboxing, and observability. The model weights are not the harness. And in 2026, the…
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What Is Agentic AI Technology? A Practitioner’s Field Map of the Enterprise Stack
“Agentic AI technology is the software stack that lets an enterprise hand a system an outcome to achieve rather than a script to execute” © Dr. Harish Kotadia, 2026 — the model, memory, tools, identity, guardrails, and observability that turn a goal into governed, auditable action. Instructions in, results out — that was IT. Intent…
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Agentic AI: The hidden cost of NOT doing it RIGHT
Most enterprises are still running linear LLM chains and calling it “AI transformation.” Here’s what that’s actually costing you: Fact 1: Organizations running agentic workflows report up to 35% gains in operational efficiency and materially faster task execution. Your competitors aren’t waiting. Fact 2: Gartner says 40% of enterprise apps will embed task-specific AI agents…