AI Agent vs Agentic AI¶

Terminology that matters

Tool-use is not autonomy.

People use “agent” and “agentic” interchangeably — and then wonder why deployments fail. The difference is not marketing language. It is a difference in risk surface.

Governance approach Constraints & SHACL Why probabilistic AI fails

The distinction

AI agent (tool-using)

A model that can call tools (search, code, APIs) to complete a task, typically within a bounded interaction.

Agentic AI (system property)

Autonomy + iteration + memory + action loops that continue over time. If you deploy this, you are shipping a process.

What changes when a system becomes agentic

Feedback loops

Actions change the world; the world changes the next action. Errors compound.

Stopping conditions

“Keep going” is not a control policy. You need explicit stop, timeout, and escalation rules.

Governance constraints

Define what must never happen and enforce it at runtime.

Abstention

Refuse to act when evidence is insufficient or constraints fail.

Diagram: from tool-use to autonomy¶

flowchart TB;
  subgraph ToolUse["AI Agent (tool-using)"];
    U["User"] --> Q["Question"];
    Q --> L["LLM"];
    L --> T["Tools"];
    T --> L;
    L --> A["Answer"];
  end;

  subgraph Agentic["Agentic AI (system property)"];
    G["Goal"] --> P["Plan"];
    P --> X["Act"];
    X --> O["Observe"];
    O --> M["Memory"];
    M --> P;
    O --> V["Validate constraints"];
    V -->|"Fail"| S["Stop / abstain / escalate"];
    V -->|"Pass"| P;
  end;

Diagram: governance gate (the non-negotiable)¶

flowchart LR;
  A["Proposed action"] --> V["Validate constraints"];
  V -->|"Pass"| E["Execute"];
  V -->|"Fail"| S["Stop / escalate"];

Practical implication¶

If you want agentic behavior in a high-stakes domain, the core design question is:

What mechanisms prevent the system from acting on a wrong belief?

Next: Governance Approach and Constraints & SHACL.