# Agentic AI

> Agentic AI is the class of AI systems that act toward goals — planning, calling tools, and iterating on results — rather than only generating content.

**Agentic AI describes AI systems that act, not just generate: given a goal, they plan, call tools, observe outcomes, and iterate — taking actions in the world rather than returning content for a human to act on.**

The term marks a real architectural boundary, not just marketing. A generative system's output is consumed by a person; an agentic system's output is an *action* — run this command, file this ticket, edit this file — whose result feeds back into the system's next decision. That loop unlocks multi-step autonomy and introduces the discipline that comes with it: bounding what actions are allowed, [keeping humans in the loop](/glossary/human-in-the-loop) for the irreversible ones, and [securing against new attack surfaces](/guides/ai-safety/owasp-agentic-top-10).

Software engineering became agentic AI's proving ground because code has built-in verification — tests, compilers, CI — giving agents an objective signal to iterate against. The patterns that emerged there ([single agents](/glossary/ai-agent), [multi-agent orchestration](/guides/advanced/multi-agent-orchestration), [agent engineering](/glossary/agent-engineering) as a role) are now spreading to research, operations, and business workflows.

---

_Source: https://agentscamp.com/glossary/agentic-ai — Term on AgentsCamp._