If spring cleaning leaves you staring at a dozen half-finished jobs, or giving feedback to a team member leaves you rehearsing the conversation for three days, AI can help with both. The trick is not asking it to “do everything”; it is giving it enough detail to create a useful first draft while keeping the final judgment in your hands.

Try at least one before Sunday. That is the whole assignment.

Use Case 1 of 2

Use Case 1: Spring cleaning using a checklist AI creates

At 9:15 on Saturday morning, April 18, 2026, Margaret Lewis stood in the kitchen with a coffee in one hand and a roll of trash bags in the other. She had promised herself she would “get the house sorted,” but that phrase had already become a problem. Should she start with the windows? The pantry? The spare bedroom? What about the garage, where three generations of miscellaneous objects had accumulated? Margaret lives in a two-story house, works part-time, and has a bad knee, so a generic spring-cleaning list would be more discouraging than helpful. What she needed was not motivation. She needed a sensible order of operations, realistic time estimates, and permission to stop before exhausting herself.

Here is the exact prompt to use:

Copy and paste this into ChatGPT or Claude:

> I want you to create a practical spring-cleaning checklist for my home. Do not give me a huge generic list. Build the checklist around my actual circumstances. > > Home: two-story, three-bedroom house with two bathrooms, a kitchen, dining room, living room, home office, laundry room, basement, and small garage. > > People: one adult and one dog. > > Time available: two hours on Saturday morning, two hours on Sunday afternoon, and one hour on three weekday evenings. > > Physical limitation: I have a bad knee, so avoid putting all the standing, bending, lifting, or stair work on one day. Include seated or low-effort tasks as alternatives. > > Priorities: kitchen cupboards, bathroom cabinets, windows that are easy to reach, dust and pet hair, the entryway, and the garage workbench. The basement is low priority. > > Supplies I already have: microfiber cloths, a vacuum, a mop, all-purpose cleaner, glass cleaner, garbage bags, rubber gloves, and a small step stool. > > For each task, include: > 1. The room or area > 2. A clear description of what to do > 3. An estimated time > 4. Whether it is light, moderate, or physically demanding > 5. Any supplies needed > 6. What can be skipped if I run out of time > > Organize the result into five work sessions, beginning with the highest-impact tasks. Keep each session realistic and under the time available. Include a short “stop here for today” point in every session. Do not recommend mixing cleaning chemicals, climbing on furniture, or lifting anything that could injure me. If an important detail is missing, ask me no more than three questions before creating the checklist.

Why this prompt works: It gives the AI boundaries instead of asking for an imaginary perfect house. The details about rooms, available time, supplies, priorities, and the knee injury tell it what to include and what to leave out. Asking for effort levels and stopping points is especially useful: a checklist should help you make decisions, not quietly turn a Saturday morning into an endurance event. The request to ask only three questions also prevents an endless interview before anything useful appears.

Use Case 2 of 2

Use Case 2: Giving feedback to a team member

At 4:40 on Tuesday afternoon, October 20, 2026, David Chen closed his laptop after reading a project update from his team member, Laura. The report contained good work, but the important information was buried beneath several pages of background detail. David needed Laura to make the document shorter and more decisive before it went to the client on Friday. He also knew that saying “this is too long” would sound dismissive, especially because Laura had spent most of the weekend preparing it. His problem was not noticing the issue. His problem was explaining it clearly, respectfully, and specifically enough that Laura could act on it.

Here is the exact prompt to use:

Copy and paste this into ChatGPT or Claude:

> Help me prepare constructive feedback for a team member. I want the feedback to be clear, respectful, specific, and focused on future improvement - not on personality or assumptions about intent. > > Team member: Laura > > Situation: On Tuesday afternoon, Laura sent me a six-page project update that will be adapted for a client presentation this Friday. > > What I observed: The report includes accurate research and several useful recommendations, but the main conclusion does not appear until page five. The first four pages contain background information, repeated points, and details that the client probably does not need in the presentation. I have not yet discussed this with Laura. > > Impact: I am concerned that the client may miss the recommendation, that the presentation may run over time, and that Laura may spend another day polishing material that will be removed. > > What I want instead: A one- or two-page executive summary that begins with the recommendation, followed by only the evidence needed to support it. The detailed research can remain in an appendix. > > Context: Laura is conscientious and technically strong. I want to recognize the quality of her research while explaining that the document needs to be more concise for this audience. > > Please produce: > 1. A short version I can say in a private conversation > 2. A warmer, more conversational version > 3. A written follow-up message > 4. Two questions I can ask Laura to understand her perspective > 5. One specific next step we can agree on before Friday > > Use this structure: situation, observable behavior, impact, desired approach, and next step. Avoid words such as “careless,” “confusing,” “too much,” or “you always.” Do not invent motives or facts. Flag any sentence that sounds like a judgment rather than an observation.

Why this prompt works: It separates what David saw from what he fears might happen. That distinction matters. Strong feedback usually names the situation, describes observable behavior, explains the impact, and identifies a next step; it does not label someone’s character. The prompt also asks for several formats, questions, and a follow-up action, which turns AI from a speechwriter into a preparation partner. Laura still gets a chance to explain her choices.