Module 1 • 22 min
AI Agents vs. Agentic AI
Clarify the system being proposed and the autonomy it will actually have.What This Decision Controls
AI agents are systems designed to handle a specific, bounded task or workflow. They usually operate within a defined set of tools, data, instructions, and escalation rules, such as classifying a support request, checking account status, qualifying a lead, or retrieving an approved knowledge answer. The aim is reliable execution inside a known operating boundary.
This decision affects the reliability, cost, governance burden, and operating value of the agent long after the first demonstration.
How to Evaluate It
Agentic AI describes a system with broader autonomy to plan and coordinate multi-step work toward a goal. It may choose among tools, create intermediate plans, maintain context across steps, and adapt its next action as new information appears. That flexibility can be useful for complex work, but it also creates more opportunities for unexpected behavior. Start with a specific, bounded AI agent when possible, then justify any move toward multi-step agentic behavior with a real workflow need, defined controls, and a recovery path.
Work from a real workflow and real constraints. A technically possible design is not automatically the right operating design for your organization.
Decision Checklist
- State the business outcome and the bounded task the agent must support.
- Identify the accountable business owner, technical owner, and required human reviewer.
- Confirm the data, integrations, escalation path, and metric required before a build decision.
Worked Decision Scenario
A support team wants an assistant to handle account-status questions and automatically open a case when information is missing. The work is repeatable, the tools are known, and an escalation path already exists, so a bounded AI agent is the appropriate starting point.
The team does not begin with an agentic system that plans across several departments. It first proves the specific workflow, then expands autonomy only if a measurable need remains after the controlled version is operating safely.
Apply it
Architecture Exercise
Classify one proposed agent use case.
Saved locally for this review prototype. Your response will become private account data when the approved course backend is connected.