Create a human-sustainability checklist for a team workflow
Produces a checklist to review a workflow for pace, workload, handoffs, after-hours demands, and recovery so it works for people long term.
The prompt
Help me create a checklist to check whether a workflow is sustainable for the people who run it.
Workflow: [e.g. "monthly close", "customer escalation handling", "content production"]
Steps and who does them: [PASTE OR DESCRIBE]
Volumes, deadlines, and service levels: [DETAILS]
Tools and automation involved, including AI: [DETAILS]
Known pain points: [e.g. "weekend work at month-end", "one person is the only expert"]
Build a checklist grouped into these areas, with yes/no questions and a note on what "good" looks like for each:
1. Workload and pace: realistic volumes, peaks planned for, buffers in deadlines.
2. Hours and boundaries: after-hours or weekend demands, on-call fairness, time-zone load.
3. Single points of failure: knowledge held by one person, cover for leave.
4. Cognitive load: number of tools, context switches, unclear handoffs, manual tracking.
5. Autonomy and clarity: clear owners, decision rights, priorities.
6. Automation and AI effects: whether automation removed work or added checking and coordination.
7. Recovery and recognition: time to recover after peaks, credit for invisible work.
Then:
- Apply the checklist to my workflow and mark each item green, amber, or red based on what I've shared, or "unknown" if I haven't said.
- List the top 3 fixes with an owner and a first step.
- Suggest how often to rerun the checklist.
Keep it neutral and practical. For changes affecting hours, pay, or contracts, note that HR and local employment law should be checked.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Leadership & Management prompts
What to fill in
- PASTE OR DESCRIBE
- DETAILS
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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