Where an AI agent helps—and where clear rules are enough.

1. Start with the predictable steps.

A workflow follows an explicit sequence: receive an input, check a condition, perform an action, and record the result. If your team can describe the decision as a stable rule, that rule is often the clearest starting point.

Consider assigning requests by region or copying an approved order into another system. These steps need consistent execution and reliable error handling. Adding interpretation where none is needed can make the process harder to explain and test.

2. Identify the parts that need interpretation.

An AI component can help with variable language: summarizing a long enquiry, suggesting a category, or extracting relevant details from a message. An agent may also choose among permitted steps according to the task and available context.

This flexibility needs boundaries. Define what information the system can use, which tools it can access, and which actions require approval. A plausible answer is not the same as a correct record update or an authorized external action.

3. Combine rules with limited interpretation.

Many useful systems are hybrids. A fixed workflow receives a support request, an AI step suggests a category and drafts a summary, and explicit rules route the result to a review queue. The original message remains available so a person can inspect the source.

Keep the interface between steps clear. Specify the expected fields, acceptable values, and the response when information is missing. If a result fails validation, send it for review rather than forcing it into the next step.

• Use clear rules for permissions, routing, and required fields.
• Use interpretation for bounded language tasks with examples.
• Keep approval before actions whose mistakes would be costly.

4. Test the difficult cases, not just the demo.

Collect examples that include ambiguous wording, incomplete details, conflicting instructions, and requests outside the intended scope. Decide what a safe and useful response looks like for each one before testing.

Evaluate the result of the whole task. A good summary is not enough if it routes to the wrong person. Check whether the reviewer has enough context, whether rejected output is visible, and whether repeated processing creates duplicates.

5. Choose the simplest system you can maintain.

Ask who will update the rules, review exceptions, and notice changes in output quality. Factor that operating work into the choice alongside build effort and expected benefit.

Start with limited permissions and a small set of actions. Expand when the team has evidence that the system behaves as intended and can recover when it does not. The best architecture is the one that fits the work and remains understandable to its owners.