PlaybookPrompts

Design a focused reading list for onboarding to a new domain

Education & Learning onboardingreading-listdomain-learningself-directed-learning

When you move into an unfamiliar domain — new industry, new function, new tech stack — a pile of links helps no one. This prompt builds a sequenced reading plan with explicit rationale for each item's order and purpose.

Prompt
I'm onboarding to {{NEW_DOMAIN}} as a {{JOB_ROLE}}. I need to be functional enough to contribute in {{TIMEFRAME}} (e.g., 2 weeks, 30 days). My existing background is {{EXISTING_BACKGROUND}}.

1. Identify the 4-5 core concepts someone must understand to operate in {{NEW_DOMAIN}}. For each, write one sentence explaining why it's foundational and what goes wrong if you skip it.

2. Build a sequenced reading plan with exactly 8 items total. Each item should be:
   - A type of source (e.g., 'official documentation overview', 'practitioner post-mortem', 'introductory textbook chapter', 'annotated worked example') rather than a specific URL or book title (links go stale; source types don't).
   - Labeled with its position in the sequence and a reason it belongs at that position.
   - Matched to one of the core concepts from step 1.
   - Accompanied by a guiding question I should be able to answer after reading it.

3. Flag 2 common onboarding mistakes people make when learning {{NEW_DOMAIN}} on their own (e.g., going too deep on theory before touching practice, ignoring naming conventions that cause confusion later).

4. Suggest one low-stakes practical exercise I can do after item 4 to pressure-test my understanding before continuing.

Note: This plan is for orientation, not mastery. If {{TIMEFRAME}} is shorter than 2 weeks, tell me which 4 items to prioritize and which to defer.
Variables to fill in
  • {{NEW_DOMAIN}}
  • {{JOB_ROLE}}
  • {{TIMEFRAME}}
  • {{EXISTING_BACKGROUND}}

How to use this prompt

  1. Copy the prompt above (Copy button on the top-right).
  2. Replace each {{VAR}} with your own value. Variables: {{NEW_DOMAIN}}{{JOB_ROLE}}{{TIMEFRAME}}{{EXISTING_BACKGROUND}}.
  3. Paste it into one of the recommended tools below.
  4. Iterate: tighten constraints in the prompt if the output is generic.

Why this prompt is structured this way

The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.

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