Workload check-in template
When to use: when a team member is showing signs of overload, or before a busy season. How to use: give AI what you've noticed — not who they are — and get a conversation template that opens the topic without triggering defensiveness.
When to use this prompt
Reach for this prompt when you need to when to use: when a team member is showing signs of overload, or before a busy season. How to use: give AI what you've noticed — not who they are — and get a conversation template that opens the topic without triggering defensiveness. It's designed for Line Manager. Typically used within People work.
Draft with AI, then have a colleague verify facts and tone before use.
How to use it
- 1
Gather your inputs
Have your local context, audience and goal to hand. - 2
Fill in the template
Copy the template below and replace every bracketed placeholder with real, local context. Keep names and safeguarding details out. - 3
Run it in your AI tool
Paste into your preferred AI assistant. Ask a follow-up if the output misses your association's tone or context. - 4
Review with the checklist
Work through the human-review checklist below before you send, publish or act on the output.
Prefer a guided flow? Adapt with the guided builder — it fills placeholders from your association profile.
Prompt template
Draft a workload check-in for a team member. What I've noticed (no personal detail): {SIGNS}. I want to open the conversation, not accuse. Structure: what I've noticed in behavioural terms, my hypothesis stated as a question, invitation to share their view, options for reshaping workload (drop / delay / delegate / do differently), what happens next. Warm, respectful, plain. No jargon.Replace bracketed placeholders with real context. Never paste identifying details about children, health or safeguarding cases.
Worked example
Signs: staying late 3 nights this week, cancelled 1:1 twice
What good output looks like
A calm conversation template that opens workload as a shared problem, not a performance issue.
Why this prompt works
Separates observation from interpretation and gives the team member real options.
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