You want to explore a better client handoff, so the easiest example seems to be yesterday's client file. It contains much more information than the exercise needs.
For an early AI drafting or learning exercise, build an explicitly fictional case from scratch where real client information is unnecessary. Preserve the operating pattern you want to explore while inventing names, values and events. This creates practice material, not an anonymised client record or evidence of actual results.
Photo by Diana Polekhina on Unsplash.
Define what the example needs to demonstrate
Write the question first. If you want to explore how a missing input affects a handoff, you may need a trigger, required item, owner and consequence. You probably do not need a client's exact messages, prices or distinctive circumstances.
Use the smallest scenario that makes the mechanism understandable. A rich backstory can distract from the task and tempt the assistant to infer details that were never part of the exercise.
Keep any real source material in its authorised location. Do not ask an unapproved service to transform a private record merely because the intended output is fictional.
Build a scenario card
Specify:
Fictional organisation and ordinary working context.
Task being explored.
Relevant inputs and responsibilities.
One important complication.
Facts deliberately left unknown.
Expected type of output, without prescribing the answer.
Choose details independently rather than changing only the names in a real case. A familiar combination of dates, events and roles can still reveal the underlying situation.
This is practical scenario design. It does not establish legal anonymisation, privacy compliance or suitability for sharing sensitive information.
An illustrative missing-input case
Create a fictional design studio preparing a welcome pack. The pack needs an approved service description, but the request contains two versions without an owner decision.
The exercise asks AI to prepare a clarification note and identify what can proceed. Invent the studio name and version labels. Do not add a real client's distinctive commercial terms to make the scenario feel credible.
The important pattern is conflicting sources and an unresolved owner decision. It can be explored without recreating an actual engagement.
Keep the fiction visible in every handoff
Label the example and any numerical working as illustrative. If the assistant writes a case-study style account, correct it before the material reaches a presentation or article.
Do not turn a generated outcome into evidence that the proposed process will work. Practice material can reveal questions and support discussion, but a real implementation needs evidence from its own authorised setting.
Move to real work deliberately
Once the exercise clarifies the approach, decide whether a permitted evaluation with appropriate business material is necessary. Keep that decision separate from the fictional rehearsal.
Save the reusable scenario with its learning purpose and limitations. A good example makes the operating question easier to understand while avoiding the unnecessary use of a client file.
For related practical guidance, see building a representative evaluation set and limiting information to the actual task.
Hili Consulting can help build a clearly fictional business example for a bounded AI exercise. Arrange a free 30-minute consultation and bring one example of the work you want to improve.
