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design-thinking

Use for design thinking, or when a product or service problem needs user understanding before solutions: "what do users really need?", "how might we...", "plan a discovery sprint", "validate this concept". Skip when the spec is frozen or the task is code maintenance.

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Design Thinking

Fall in love with the problem, not the first solution. End with what to learn next, not just ideas.

When to use

  • A product, service or UX problem where the real user need is unclear.
  • "How might we" framing, discovery sprints, concept validation before building.
  • Reframing a request using what users actually do or say.

Skip: the spec is fully frozen and no discovery is wanted, or the task is code-only maintenance with no user problem to frame.

Before you start

  1. State in one block: Design challenge (who is affected, in what situation) and Pass (Empathize, Define, Ideate, Prototype, Test plan).
  2. Gather first. Read tickets, interview notes, support threads, analytics or the product itself before writing Empathize. Ask up to 3 questions only for users, constraints or success signals that tools cannot answer.
  3. Light path. Small ask: 1-2 lines per stage, 3 ideas, one prototype, 2 signals.
  4. If Empathize has no real user input, say so in Define and keep the POV narrow. Never invent research.

Stages

1. Empathize

  • Who: primary user or stakeholder. Mark facts from the user versus [INFERRED].
  • Jobs, pains, gains: what they are trying to do and what hurts.
  • Context: when and where the need shows up.

No fabricated quotes. Paraphrase only what the user supplied.

2. Define

  • Insight: a non-obvious tension connecting pains and context.
  • POV: "[User] needs [verb] because [insight]."
  • How Might We: 2-3 well-scoped questions opened by the POV.

3. Ideate

Quantity and variety, using each HMW as a prompt. Tag each idea desirable, feasible or viable as a hypothesis, not a fact. Default 8-10 ideas unless the user sets a number.

4. Prototype

Describe low-fidelity artifacts: paper flow, roleplay script, landing-page smoke test, clickable sketch. For each: Purpose: the question it answers. Fidelity: one line placing it between sketch-only and interactive.

5. Test plan

  • Learning goals: what would convince you the idea is wrong?
  • Participants: who and how many, or "to be decided".
  • Signals: behaviors or metrics to observe, stated so they can fail.
  • Next iteration: what changes if results are mixed.

Pitfalls

  • A POV that restates the solution ("users need a dashboard").
  • HMW questions that are too broad ("improve the experience") or too narrow (they hide the solution).
  • Treating desirable / feasible / viable tags as proven.
  • A Test plan with no signal that could show the idea is wrong.

Worked example: references/example.md.

Checklist

  • Challenge and Pass stated
  • Empathize separates facts from [INFERRED]
  • POV and HMW before Ideate
  • Ideas tagged desirable, feasible or viable as hypotheses
  • Prototype gives purpose and a fidelity line
  • Test plan has learning goals and falsifiable signals

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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概要と使いどころ

Use for analytical thinking, or when a question needs breaking down and evidence: "why did metric X drop?", "what drives this?", "break this down", "what data do we need?". Builds a tree, hypotheses and evidence, ends with an answer and key uncertainty. Skip for quick verdicts.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for creative thinking, or when the user wants many fresh options before choosing: "give me ideas", "brainstorm names", "other ways to do this", "think outside the box". Diverges first, then picks. Skip when one answer is wanted or the task is pure execution.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for critical thinking, or when the user wants a claim, plan or decision checked for weak spots: "is this right?", "what am I missing?", "poke holes", "sanity check", "devil's advocate", "red team this". Skip for execution-only tasks and wording edits.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for ethical thinking, or when a plan could harm or unfairly burden people: "should we do this?", "is this fair?", "privacy or bias risk", "who gets hurt?". Maps stakeholders, harms, power and consent. Skip for legal advice, neutral fact lookups and implementation-only work.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for Fermi estimation, or when a rough number is needed fast: "roughly how many...", "ballpark the cost", "estimate capacity or market size", "is this even feasible?". Decomposes, uses ranges and sanity-checks. Skip when exact data is available or a precise calculation is wanted.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

Use for first principles thinking, or when the user questions an inherited default: "why do we do it this way?", "is this cost really necessary?", "should we copy what competitors do?". Strips analogies and rebuilds from fundamentals. Skip for convention-following checklists.

日本語の概要は準備中です。原文の説明を表示しています。

ysskrishna/ai-agent-skills122026年10月8日 更新

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