Introduction
A recommendation memo is a hard case for AI assistance. The assistant can produce a polished memo in seconds, and the person who signs it still has to answer questions about it in the meeting.
This walkthrough follows one manager through a division of labor in which she writes the argument and the AI summarizes and criticizes. The manager, the two systems, and every output are invented for the example.
The Starting Point
Dana manages operations for a company with four warehouses. Her director has asked for a one-page memo recommending one of two staff scheduling systems, called here System A and System B.
She has about nine pages of notes: her observations from two vendor demonstrations, feedback from supervisors at the two sites that tried each system for a month, and a cost comparison. Before using an AI assistant, she removes the supervisors' names and replaces the contract prices, which her company keeps private, with "lower" and "higher."
System A costs less and is simpler. System B costs more and lets staff swap shifts from their phones. She hasn't decided.
Walking Through the Memo
Step 1: Decide the division
Dana first decides who does what. The memo will carry her name, and her director will ask why she chose as she did. So the argument has to be hers: which system, and for which reasons.
Two parts of the job are different in kind. Condensing nine pages of notes is slow and mechanical. Finding the holes in her own argument is something she's poorly placed to do, since she wrote it. She gives those two jobs to the AI and keeps the drafting.
This is the pattern Ethan Mollick, a professor at the Wharton School, calls Centaur work, with "a clear line between person and machine" (Mollick 2023). The line here runs between the argument and the two jobs on either side of it.
Step 2: Have the AI summarize the notes, and check the summary
She pastes in her notes and asks for a summary organized by system, with the supporting passage quoted for each point.
The summary is clear and well organized. She checks it against her notes point by point. Two problems turn up. It reports that supervisors "found System B's phone app easy to use" and leaves out a note that the app lost its connection in one warehouse's loading area. It also merges the two sites' feedback on System A into a single favorable statement, when one site was favorable and the other mixed.
Neither problem is an invention. Both are selections, and both tilt the picture. She corrects the summary by hand. A summary has to choose what to drop, and she now knows what this one dropped.
Step 3: Draft the recommendation unaided
With the corrected summary beside her, Dana closes the assistant and writes the memo herself. It takes about twenty-five minutes and comes to 280 words.
She recommends System B. Her reasons are that shift swaps are the supervisors' biggest daily burden, that System B handles them without a supervisor's involvement, and that the higher price is justified by the supervisor time saved.
The draft is rougher than what the assistant would have produced. It's also a position she arrived at by weighing her own notes, and she can explain each step.
Step 4: Ask for the three strongest objections
She opens a new conversation, pastes in her draft and the corrected summary, and writes: "Here is a recommendation memo and the notes it's based on. Give me the three strongest objections a skeptical director would raise. Don't rewrite the memo."
She asks for the strongest objections on purpose. A plain request for feedback tends to bring back praise with a few gentle suggestions. She tells it not to rewrite because she wants the weaknesses named and the wording left to her.
The assistant returns three objections.
- The memo claims that saved supervisor time justifies the higher price and gives no estimate of how much time is saved.
- The memo doesn't mention that the phone app lost its connection in a loading area, which bears directly on the feature the recommendation rests on.
- System B doesn't connect to the company's payroll software, so hours would have to be entered twice.
Step 5: Revise for the objections that hold, and record the rest
Dana judges each objection against her notes.
The first holds. She has the numbers: supervisors at the trial site estimated four hours a week on swaps. She adds that figure and what it implies.
The second holds, and it stings, because she knew about the connection problem and left it out. She adds a sentence stating the problem and the vendor's proposed fix, and she makes the recommendation conditional on the fix being tested at that site.
The third is wrong. Her notes from the demonstration say that System B connects to the payroll software, and she finds the passage. The assistant stated the objection confidently and without support. She rejects it and writes one line in her own file recording why, in case the director raises the same point.
She revises the memo herself. The recommendation is still System B, now with an estimate and a condition attached.
Key Considerations
The common mistake with a memo like this is to ask the AI for the draft first. A drafted memo arrives with a recommendation, an order of reasons, and a tone already chosen. The writer then edits and ends up defending a frame they didn't choose and may not have reached on their own. Had Dana started that way, she might have recommended System A because the draft did.
Checking was part of the work at both ends. The summary left things out, and one of three objections was false. A 2025 survey of 319 knowledge workers found that people working with generative AI described their critical thinking as shifting toward verifying information and overseeing the task (Lee et al. 2025). Dana's two checks are examples of that shift. The survey rests on people's own reports, so it describes how they saw their work and doesn't measure its quality.
This is one sound division of labor among several. A different manager might write an outline, have the AI draft from it, and revise heavily. What matters in any version is that the person who signs the memo can say where each judgment came from.
Summary
Dana wrote the argument, used the AI to summarize her notes and to attack her draft, and checked both outputs against her notes. The table shows who did each step and what was checked.
| Step | Who did it | What was checked |
|---|
| 1. Decide the division | Dana | Which parts carry the judgment |
| 2. Summarize the notes | AI | The summary against the notes; two omissions corrected |
| 3. Draft the recommendation | Dana | Nothing yet; the draft is her own position |
| 4. List three objections | AI | Each objection against the notes |
| 5. Revise and record | Dana | Two objections accepted, one rejected with the reason written down |
Result: a one-page memo recommending System B, with an estimate of supervisor time saved and a condition that the connection problem be fixed and tested. Dana wrote every sentence. The AI's contributions were a summary she corrected and two objections she accepted.
References
- Lee, Hao-Ping (Hank), Advait Sarkar, Lev Tankelevitch, Ian Drosos, Sean Rintel, Richard Banks, and Nicholas Wilson. 2025. "The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers." In CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. New York: ACM. doi:10.1145/3706598.3713778.
- Mollick, Ethan. 2023. "Centaurs and Cyborgs on the Jagged Frontier." One Useful Thing, September 16, 2023.