ThinkWithPrompt by SynotticThinkWithPrompt

Equip managers to reinforce training before and after

A manager toolkit with pre-training conversation guide, post-training check-ins, and on-the-job practice ideas to make learning stick.

Leadership & ManagementFew-ShotStandardLeadershipResearchCodeFill-in Template

The prompt

Create a manager toolkit so managers reinforce a training program with their team members. Program: [NAME, FORMAT, DATES] Objectives and target behaviors: [WHAT PEOPLE SHOULD DO DIFFERENTLY] Participants and their managers: [ROLES, how busy managers are] Barriers to applying the learning at work: [e.g. "no time to practice", "old process still rewarded"] How much time managers will realistically give: [e.g. "15 minutes before, 3 check-ins after"] Research on training transfer shows the manager's involvement before and after is one of the strongest predictors of whether learning is used. Keep everything brief and easy for a busy manager. Return: 1. A one-paragraph email from L&D to managers explaining why their role matters and what we are asking (with time required). 2. A 10-minute pre-training conversation guide: questions to set goals and expectations with the employee. 3. A post-training debrief guide (within one week). 4. Check-in prompts for weeks 2, 4, and 8 tied to the target behaviors. 5. On-the-job practice assignments managers can give, with what good looks like. 6. A simple observation checklist to give specific feedback. 7. What managers should avoid (e.g. pulling people out of sessions, "forget what they told you").

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • NAME, FORMAT, DATES
  • WHAT PEOPLE SHOULD DO DIFFERENTLY
  • ROLES, how busy managers are
  • e.g. "no time to practice", "old process still rewarded"
  • e.g. "15 minutes before, 3 check-ins after"

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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