Concrete workplace scenario
A team sees many repeated tasks and wants to know which ones are worth turning into workflows first.
The trap is choosing tasks because they are annoying. D62 selects repeated tasks by frequency, risk, evidence availability, owner clarity, and payoff.
Worked answer
Bad example first: the plausible shortcut fails
Weak example
“Candidate: the task everyone finds annoying.”
What goes wrong
The weak version contains annoying, everyone, no frequency, no owner clarity.
Work-ready version: use the day rule
Frequency
How often the task repeats.
Risk / evidence
What can go wrong and what proof exists.
Owner clarity
Who can approve or stop it.
Quick decision check
Workflow candidates need repetition + risk + owner clarity
Use this rule before filling the build table. The goal is a decision-ready artifact, not a broad summary.
Frequency
How often the task repeats.
Risk / evidence
What can go wrong and what proof exists.
Owner clarity
Who can approve or stop it.
Workflow/SOP foundation week workflow trace
Before / after: what changed in your work?
Before learning
After learning
What AI-in-workflow means today
Workplace case
After defining workflow anatomy, the worker must choose which repeated task is worth mapping first instead of turning every annoyance into a workflow.
Main learning job
Identify repeated task candidates and rank them by frequency, stability, evidence availability, handoff value, and risk.
Failure mode
Choosing the most annoying task rather than the most repeatable and reviewable workflow candidate.
Row/time guidance
Core: 3 candidates; Deep: improve the same 3 candidates with stronger evidence, limits, and repair notes. Choose by repetition, input stability, owner, evidence, handoff value, and risk.
Artifact handoff
Previous artifact: D61 workflow_foundation_note.md
Next artifact: D63 workflow_io_definition.md
Learning checkpoint: Keep the handoff useful to the next lesson by naming evidence, limitation, owner, and stop rule.
Learning checkpoint
This page keeps Day 62 connected to the surrounding course path. Use the previous artifact as working input, produce today's artifact, and hand it to the next lesson with limitations visible.
Repeated-task candidate ranking
Compare three repeats: weekly renewal-risk review, ad hoc executive questions, and quarterly policy interpretation. The best candidate repeats often, uses stable inputs, and has bounded risk; policy interpretation is repeated but too judgment-heavy to workflow first.
Pick / hold / reject
Pick the task with stable inputs and a known owner. Hold tasks with variable evidence. Reject tasks where each run requires new authority or policy interpretation.
Static card version of the worked example
Use these cards before the wide table so the example does not depend on horizontal scrolling.
Worked move
Repeated-task candidate ranking
Decision standard
Pick the task with stable inputs and a known owner. Hold tasks with variable evidence. Reject tasks where each run requires new authority or policy interpretation.
Day-specific completed sample row
| No. | Candidate task | Frequency | Input stability | Decision owner | Evidence available | Handoff value | Risk / sensitivity | Candidate decision | D63 input-output need |
|---|---|---|---|---|---|---|---|---|---|
1 | Weekly renewal-risk update | Weekly | Mostly stable | Sales ops lead | Strong / traceable | High | Medium | Promote to D63 | Define required input packet and manager-ready output |
Build repeated_task_candidates.md
Core: 3 candidates; Deep: improve the same 3 candidates with stronger evidence, limits, and repair notes. Choose by repetition, input stability, owner, evidence, handoff value, and risk. Blank required fields create export warnings.
| No. | Candidate task | Frequency | Input stability | Decision owner | Evidence available | Handoff value | Risk / sensitivity | Candidate decision | D63 input-output need |
|---|---|---|---|---|---|---|---|---|---|
| 1 | |||||||||
| 2 | |||||||||
| 3 |
Summary / decision
Downstream handoff field
Repair one weak row
Use this pass to find the row that would make the artifact look ready while hiding evidence gaps, unclear owner decision, missing exception, or weak handoff.
Repair example
Weak row: Candidate chosen because it is annoying.
Repair move: Add frequency, evidence, risk, owner, and payoff.
Better row: Candidate: weekly renewal-risk review; repeats weekly; evidence exists in CRM; owner CS manager; risk unsupported claim.
Choose the row you would be comfortable carrying into the next day.
Choose the row most likely to fail before AI use.
Sentence starter: The weak row is weak because ___. I will repair it by adding ___ before using AI.
Export artifact
This file is today’s work receipt. It should show the exact decision or handoff that the next day can use, not just that you filled a table.
Before you export
- Does the export justify candidates by frequency, risk, evidence, owner, and payoff?
- Does it avoid choosing only the most annoying task?
- Would D63 know which candidate needs input/output definition?
What this artifact proves: This file proves the learner can select repeated task candidates that deserve workflow design.
Weak export: Candidate chosen because it is annoying.
Good export: Candidate: weekly renewal-risk review; repeats weekly; evidence exists in CRM; owner CS manager; risk unsupported claim.
Click Generate Markdown to create repeated_task_candidates.md.