ThinkWithPrompt by SynotticThinkWithPrompt

Break a new skill into sub-skills and decide what to learn first

A map of the parts of a skill, the few that matter most for your goal, and a benchmark to measure progress.

Learning & TeachingFew-ShotAdvancedFill-in TemplateStep-by-step

The prompt

Help me break a skill I want to learn into its parts and decide where to start. Skill: [WHAT - e.g. "public speaking", "watercolor painting", "financial modeling in Excel"] Why I'm learning it: [GOAL - e.g. "present at work without notes", "sell prints online"] What "good enough" looks like in 90 days: [A CONCRETE THING I WANT TO BE ABLE TO DO] What I can already do: [CURRENT LEVEL and any related skills] Time available: [HOURS PER WEEK] Steps: 1. Split the skill into 6-12 sub-skills. For each, say whether it is foundational (other sub-skills depend on it) or advanced. 2. Apply an 80/20 test: mark the 3-4 sub-skills that will produce most of my 90-day result. 3. Flag sub-skills I can postpone or skip for now, and say why. 4. Name the most common beginner mistakes and plateaus for this skill. 5. Define one simple benchmark task I can repeat on day 1, day 45, and day 90 to measure progress, with a way to score it. Return: - A table: Sub-skill | Foundational or advanced | Priority (now / later / skip) | Why. - The 3-4 focus sub-skills in the order I should learn them. - The benchmark task and its scoring method. - Beginner pitfalls to watch for. - A one-line reality check: is my 90-day goal realistic for my hours? If not, suggest a smaller version. This is step 1 of the "Teach yourself a new skill in 90 days" pack. The focus list and benchmark are the inputs for step 2 (choosing resources).

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

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What to fill in

  • A CONCRETE THING I WANT TO BE ABLE TO DO
  • CURRENT LEVEL and any related skills
  • HOURS PER WEEK

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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