ThinkWithPrompt by SynotticThinkWithPrompt

Turn our team's documents into an onboarding guide for new hires

Turns a pile of team documents, wikis, and notes into a structured onboarding guide with what to read, learn, and do in the first 30 days.

HR & HiringFew-ShotStandardAnalyzeFill-in Template

The prompt

Turn our existing materials into an onboarding guide for someone joining my team. Role joining: [e.g. "junior financial analyst"] Team and what we do: [SHORT DESCRIPTION] Materials: [PASTE or list documents, wiki pages, process docs, slides, glossaries, org charts - with titles] What new hires struggle with most: [e.g. "our acronyms", "knowing who to ask", "the month-end process"] First-month goals: [what they should be able to do by day 30] Build the guide: 1. Welcome and the big picture - what the team does, who our customers or stakeholders are, and how this role contributes. 2. Week-by-week plan for the first 30 days: what to read (from my materials, in priority order), who to meet, what to practice, and a small task to complete each week. 3. Must-read vs. read later - sort every document I gave you, with one line on why it matters. 4. Key processes - a short summary of each core process, with a link to the source document. 5. Glossary - acronyms and team terms found in the materials. 6. Who to ask for what - based on the materials; leave [ADD NAME] where unclear. 7. Self-check questions - 8-10 questions a new hire should be able to answer by day 30. 8. Gaps - topics a new hire will need that my materials don't cover. Use only what's in the materials for processes and facts; flag anything that looks outdated as [CHECK IF CURRENT].

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

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What to fill in

  • e.g. "junior financial analyst"
  • SHORT DESCRIPTION
  • what they should be able to do by day 30
  • ADD NAME
  • CHECK IF CURRENT

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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