What Is Agentic AI?
An agent can plan a multi-step task, decide which tools or data sources to use, and execute and adapt its actions along the way, often without a human approving each step. This is no longer theoretical: coding agents, browser agents, and task-automation agents are already in production, frequently connected to internal systems through protocols like MCP. That autonomy is the point, and it's also what expands the attack surface. Every tool an agent can call and every action it can take without a human in the loop is a new place for something to go wrong. As agentic systems take on more real work, the security conversation shifts from "is the output correct" to "what did the agent actually do, and did anyone approve it."
How It Works / Why It Matters
- Agents typically operate in a loop: observe, plan, act, observe the result, repeat, rather than a single request-response exchange.
- Autonomy and oversight trade off directly against each other. The more steps an agent completes without a human checking in, the harder it is to catch a problem before it has already happened.
- Agents are often connected to real systems (email, databases, code repositories, internal APIs) through MCP or similar protocols, so a manipulated agent isn't just generating bad text, it can take a real action.
- Guardrails for agentic systems tend to focus on scoping what an agent is allowed to touch, not just filtering what it's allowed to say.
