The difference is how the next step is chosen
A workflow follows a process you define. It may include an AI step, such as extracting fields or drafting a reply, while the surrounding sequence stays predictable. An agent can choose among available tools or intermediate steps in pursuit of a goal. Many useful systems combine both patterns.
The label matters less than whether the design fits the job. If every successful case follows the same path, a controlled workflow is often easier to inspect. If a task genuinely requires finding information and selecting an appropriate next step, a scoped agent may help.
Example: preparing a customer-support reply
A fixed workflow could classify an incoming message, retrieve an approved help article, draft a response and send it to a reviewer. An agent might decide which knowledge source to search, ask a clarifying question or request an allowed account lookup. Neither pattern needs permission to send a message automatically.
A sensible first version keeps the customer-facing action under review. Ask whether the draft is supported by a source, whether an account lookup was necessary and whether the proposed answer should be escalated. These checks make the distinction between a demonstration and an operable tool clearer.
Compare the designs before choosing
| Question | Controlled workflow | Scoped AI agent |
|---|---|---|
| Who chooses the next step? | The process definition | The agent within its allowed tools |
| What should be tested? | Each step and exception path | Tool choices, answers and handoffs |
| When is it useful? | Repeated work with a known path | Tasks requiring bounded information gathering |
| What remains necessary? | Validation and appropriate approval | Validation, limited permissions and appropriate approval |
Limit tools by what the task actually needs
Separate reading information, creating a draft and committing an action. A knowledge assistant does not need write access to every system it can describe. Where an action changes a business record, define who can approve it and how the result will be recorded.
Tool access should be specific enough to explain to the team. If an agent cannot answer a question from the permitted information, it should ask for clarification or hand the task off. More tools do not automatically produce a more reliable assistant.
Build an evaluation set around real failure modes
- A question with no answer in the approved knowledge base.
- Two documents that disagree or have different dates.
- A request outside the assistant's defined purpose.
- A tool timeout or incomplete result.
- An action that requires approval rather than immediate execution.
Keep the deployment observable
Record the important steps without copying unnecessary personal information into logs. Review unresolved tasks and incorrect tool choices, not just the final answer. Set timeouts and usage limits so a failed task cannot keep running unnoticed.
For a first project, choose the smallest design that meets the requirement. A fixed workflow with one AI step may solve the problem. Add agent-style decision-making when it has a clear purpose and a testable boundary.
Practical guidance with illustrative examples. Prepared with AI assistance; no customer results or performance claims are implied.
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