think-far-analogy-ideation

name	think-far-analogy-ideation
description	Generates novel solution candidates by stating a problem's deep relational structure, mapping it to distant source domains (nature, other industries, games), and transferring the mechanism rather than surface features, then adapting. Use when near, obvious solutions are exhausted and you need genuinely original approaches.
license	Apache-2.0
metadata	{"id":"thinking-framework-skills.far-analogy-ideation","family":"divergent-ideation","evidence-tier":"S","version":"0.1.0","standard":"0.8"}

Far-Analogy Ideation

Most ideation transfers solutions from near domains (products like yours), which yields obvious, low-novelty ideas. Far-analogy ideation deliberately reaches to distant domains - nature, other industries, games, history - and transfers the deep relational structure of a working solution there, not its surface features. The originality comes from the distance; the validity comes from mapping structure, not surface similarity. The output is a far-analogy transfer sheet of candidate mechanisms to adapt. The failure to avoid: surface-matching ("both involve networks"), which produces cute-but-useless analogies and carries none of the benefit.

When to Use

• Near, obvious solutions are exhausted or all look alike.
• You want genuinely original approaches, not incremental variations.
• The problem has a clear underlying structure that can be stated abstractly.

When NOT to Use

• An obvious near solution already exists and works (far analogy is overkill and riskier).
• When you need to converge and decide (use a decision skill).
• When only a surface match is available (a forced, surface-level analogy is worse than none).
• Execution tasks with no real ideation need.

Instructions

When asked to ideate by far analogy, follow these steps:

1. State the deep structure. Abstract the problem to its relational core, stripped of domain surface ("an entity must attract the right partners at low cost, then convert low commitment to high"). This is the step that makes the analogy valid.
2. Reach to distant domains. Find 2 to 3 domains far from the problem where that same structure is solved (biology, other industries, games, history). Deliberately avoid near, same-industry sources.
3. Map mechanism to mechanism. For each, describe how that domain solves the structure - the mechanism, not the surface. Flag if a mapping is structural vs at risk of being surface-level.
4. Transfer and adapt. Turn each mechanism into a concrete candidate idea for the actual problem.
5. Shortlist as candidates. Select the most promising, flagged as candidates to test (not answers), noting what would have to be true.
6. Emit the transfer sheet per references/TEMPLATE.md.

Output Format

Use the template in references/TEMPLATE.md. The deliverable is the structure, the distant sources, the transferred mechanisms, and adapted candidates, not prose.

Quality Checklist

Before finalizing, verify:

• The deep relational structure is stated abstractly before any analogy.
• Source domains are genuinely distant, not near/same-industry.
• Mappings are mechanism-to-mechanism (structural), with surface-only matches flagged or rejected.
• Each idea is a candidate to test, not presented as the answer.
• The output is the transfer-sheet artifact, not prose.

Evidence

Tier S. Distant analogies produce more original and novel solutions than near ones across creativity and design studies, and analogical transfer is a well-studied innovation mechanism (Gentner structure-mapping; Gick & Holyoak 1980; Dahl & Moreau). The honest failure mode is built in: surface-feature mapping carries none of the benefit and some risk, so the method requires mapping deep structure. Evidence is for human ideation, transferred to AI use, not AI-validated. Full grading: evidence/dossier.md.

Examples

See references/EXAMPLE.md for a completed transfer sheet.