D60 corrected v2 · Manual First

D31 Turn a vague request into a Request Intake Log

First manually capture who / what / when / why / urgency / output, keep unknowns as unknown, then let AI check for missing fields. Today’s artifact is D31 Request Intake Log Pack.

real_junior_situation: manager drops a short follow-up request
role_context: junior student success / operations assistant
manual_skill_target: capture request fields and unknowns
final_work_object: request intake log
AI use mode: manual first

Export filename

D31_Request_Intake_Log_Pack.md

Jump to export

Manual First Gate

manual_attempt: Fill in the request intake yourself first.source_boundary_check: Separate known from unknown; do not guess.ai_allowed_after: After the manual attempt, AI only checks for missing fields.human_correction: You decide what to add and what to ask.final_work_object: request intake log.

ai_may: check missing fields only. ai_may_not: write task brief first or infer missing facts. Next-stage note: read the manager task before advancing.

1. Role / Context

You are a junior assistant in Career Center / Student Success. Your manager gives a one-line task with incomplete information. Your professional skill is not writing a polished document right away; it is first capturing the request safely.

2. Work Order

Manager message:

“Before tomorrow afternoon’s workshop follow-up, help me organize the student feedback and next prep items.”

3. Workload / Path

StepWhat you doOutput
CaptureManually identify requester / need / dueraw fields
SeparateSeparate known / unknownunknown list
CheckCheck output / source / urgencymissing fields
FinalizeWrite the intake logartifact

4. Source Materials

What is known?

What must be marked unknown?

5. Core Concept

Request Intake Log It is the first reliable record of the request. It is not the final work order; its value is preventing misunderstanding, missing fields, and overpromising.

6. Traditional vs Work-ready

Weak

“Organize the workshop follow-up.”

Work-ready

Requester: manager. Need: organize student feedback and next-session prep. Due: tomorrow afternoon. Output format, source owner, and audience: unknown.

7. AI-upgraded Workflow

What can AI do?

When AI outputs “make a memo”?

8. Worked Example

Bad: “Ask AI to write follow-up report.” → Repair: “Output format unknown; ask whether memo or checklist.”

9. Task Cards

Task 1 — Manual intake

Task 2 — Unknown check

9b. Boundary Drill

Unknown handling

Source owner

10. Quick Checks

11. Guided Practice

Repair this weak intake: “Organize feedback and give it to the manager tomorrow afternoon.”

12. Independent Practice

13. Common Mistakes

  • Treating a vague request as a complete task.
  • Letting AI guess the output.
  • Not marking unknowns.

14. Rubric / Redlines

PassRedline
known/unknown clearAI writes first
missing fields become D32 inputguess becomes fact

15. Artifact Builder

Student artifact body: exported Markdown. How this supports learning: Practice receiving tasks safely.How this is used in real work: Prevent doing the wrong work.How this is used in a portfolio: Show manual intake discipline.How to explain it to someone else: “I captured a vague request, preserved unknowns, and prepared clarification seeds.” Structure-check boundary: Structure checks confirm completion only; quality still needs human review.

16. Handoff

D31 artifact goes to D32: request intake log + missing fields → clarification message.

Standard export filename: D31_Request_Intake_Log_Pack.md

Student progress: Day 31 in the 90-day track. Complete the page, run the structure check, then copy or download the Markdown artifact.