# The Cross-Domain Prompt Library

> **One-liner:** Build a documented library of prompt patterns borrowed from 3+ different fields, with tested adaptations and transfer notes for your own domain.

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## 🔧 Jump in (Tinkerers start here)

You're going to build a personal prompt library of techniques stolen from other fields — documented well enough to teach someone else.

**Phase 1 — Survey 3 domains.** Pick 3 fields that are different from your own *and* from each other. Send this to three separate sessions:

> How do professionals in **[field]** use AI in sophisticated ways? I don't want generic "they use ChatGPT" answers. Give me 5 advanced AI techniques or prompting patterns that are specific to this field. For each:
> 1. Name the technique
> 2. Describe the prompt pattern (what input, what instructions, what output format)
> 3. Why this technique works in this domain (what problem it solves)
> 4. Example prompt (ready to use)

**Phase 2 — Select your top 5.** From the 15 techniques across 3 domains, pick the 5 that are most interesting or most likely to transfer. For each one, send:

> Analyze this technique from **[source domain]**: **[technique description]**
>
> Map the transfer potential:
> 1. **Core principle:** What's the underlying mechanism that makes this work, independent of domain?
> 2. **Direct transfer:** What would this look like applied to **[your field]** with minimal modification?
> 3. **Modified transfer:** What would need to change to make it work well in my context?
> 4. **What doesn't transfer:** What aspect is domain-specific and should be replaced?
> 5. **Adapted prompt:** Write a ready-to-use version for my field

**Phase 3 — Test each adapted prompt.** Run all 5 adapted prompts on real tasks in your work. For each, document:

| Technique | Source Domain | My Task | Result Quality (1-5) | What Worked | What Needed Adjustment |
|-----------|-------------|---------|---------------------|-------------|----------------------|

**Phase 4 — Build the library entry.** For the 3 best-performing techniques, create a library card:

> Create a "Prompt Library Card" for this technique:
>
> **Name:** [give it a memorable name]
> **Borrowed from:** [source domain]
> **Core principle:** [1 sentence — why this works]
> **Original use:** [what it does in the source domain]
> **My adaptation:** [what it does in my domain]
> **Ready-to-use prompt:**
> ```
> [the tested, refined prompt with placeholders]
> ```
> **When to use:** [scenarios where this technique is the right choice]
> **When NOT to use:** [scenarios where it fails or is overkill]
> **Transfer notes:** [what I learned about adapting this — tips for others]

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## 📋 Plan first (Planners start here)

Here's what you're about to do:

1. **Survey 3 unfamiliar domains** — Discover advanced AI techniques in three different fields. Cast a wide net — diversity of domains matters more than depth.
2. **Select the top 5 candidates** — From 15 techniques, choose 5 based on transfer potential and novelty. Look for techniques that solve a problem *structurally* similar to one in your work.
3. **Analyze transfer mechanics** — For each technique, separate the domain-specific elements from the core principle. Identify what transfers directly, what needs modification, and what should be replaced.
4. **Test all 5 adaptations** — Run each adapted prompt on a real task. Document quality, surprises, and adjustments needed.
5. **Document the top 3** — Create library cards with enough detail for someone else to use the technique without your guidance.

**"Done" looks like:** A 3-entry prompt library with tested techniques from other domains, complete with ready-to-use prompts, usage guidance, and transfer notes.

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## 🧭 Why this matters (Strategists start here)

In [CDR-Basic-01](/exercises/cross-domain-reframing/cdr-basic-01/), you borrowed a single technique. In [CDR-Intermediate-01](/exercises/cross-domain-reframing/cdr-intermediate-01/), you transplanted an entire framework. Here, you're building a **systematic practice** — a personal library that compounds over time. The library card format forces you to articulate *why* a technique transfers, which is the meta-skill: once you can spot the structural similarity between domains, you can generate new cross-domain adaptations on your own. This library also becomes a shareable team asset — a collection of non-obvious AI techniques that others in your field won't have discovered.

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## Reflection

- Which of the 3 domains produced the most transferable techniques? Why?
- Did any technique work *better* in your domain than in its original domain? What does that tell you?
- What pattern do you notice in what transfers well vs. what doesn't? Can you articulate a rule of thumb?
- 💬 *Share your prompt library with colleagues and have them test the techniques on their own tasks. The techniques that work across multiple people's contexts are genuinely domain-agnostic — those are your keepers.* (Social Learners)

## ⬆️ Level up

You've reached the advanced level for Cross-Domain Reframing. From here, consider:

- Expanding the library monthly — add one new cross-domain technique per month from a new field
- Sharing the library with colleagues and collecting their transfer notes
- Combining this with [WA-Advanced-01](/exercises/workflow-automation/wa-advanced-01/) to build cross-domain techniques into automated workflows

Back to [Cross-Domain Reframing](/pillars/cross-domain-reframing/)