Build a testable workflow and evaluate where AI fits.

A useful automation handles a defined task. Begin with a process you can explain on paper, such as placing incoming requests in the right review queue. If you cannot say what a correct result looks like, you are not ready to automate it.

Draw five boxes: Input, Validation, Rule, Review and Output. Input is what arrives. Validation checks required fields. A rule handles a predictable case. Review is where a person decides an uncertain or consequential case. Output is the saved result. For this exercise, no box sends a message, accepts a booking or makes a payment.

Use invented records with three fields: Request ID, Request text and Preferred date. The first rule checks whether Request ID and Request text exist. A record with a missing field goes to Needs details. A repeated Request ID goes to Duplicate review. All other records go to Owner review. Write the rule in plain language before using any automation tool.

Where could AI help later? It might suggest whether free text describes a quote request or a support question. That is a suggestion, not permission to send a reply or follow instructions embedded in the text. A simple dropdown or rule may be sufficient. Record what extra value the AI would need to demonstrate to justify its cost and errors.

Test the process manually with a normal request, an empty text field, a duplicate ID, an unclear request and a request containing an instruction to ignore the rules. The last record is customer content to classify, not a command to operate your system. Document the expected queue and whether your rule produced it.

This first lesson creates a workflow specification. It does not create a running AI agent. A later implementation needs actual platform checks, permissions, cost limits and failure testing before a business can rely on it.

Worked example

Fictional example: Ravi receives PRACTICE-01 with Please quote a video clip and a date. It goes to Owner review. A second PRACTICE-01 goes to Duplicate review. PRACTICE-03 has no request text and goes to Needs details.

His proposed pilot is an inquiry-routing demonstration using invented data. Its output is a review queue and test log. No inquiry is answered automatically, no customer record is uploaded and no saved time or income is claimed.

Your exercise

1. Draw the five-box workflow.
2. Name the required fields and the three review queues.
3. Write your missing-field and duplicate rules.
4. Create five synthetic records covering the test cases above.
5. Run each record through the rules by hand and record expected versus actual results.
6. Write one sentence explaining whether an AI suggestion would improve this particular task. Save the map and test log.

Check your work

• The task and correct output are defined before choosing a tool.
• Missing fields and duplicate IDs have a review path.
• Customer text cannot change the workflow's instructions.
• No message, payment or booking is made automatically.
• AI's proposed value and its possible errors are both recorded.
• No API, paid credits, credentials or real customer data are required for this lesson.