The Stolen Technique

One-liner: Take an AI technique from a completely different field and apply it to your own work — discovering that the best prompting ideas are often borrowed.

🔧 Jump in (Tinkerers start here)

Pick a field that is not your own. If you work in marketing, pick engineering. If you're a designer, pick finance. If you're a developer, pick journalism. The more unfamiliar, the better.

Step 1 — Discover a technique. Send this prompt:

How do professionals in [unfamiliar field] use AI in their daily work? Give me 5 specific, concrete techniques — not general concepts. For each technique, describe: what they prompt the AI to do, what input they provide, and what output they get. Focus on techniques that are unique to this field.

Step 2 — Steal the best one. Pick the technique that seems most interesting or most different from how you currently use AI. Then send:

I work in [your field]. Take the technique you described as #[number] — [briefly describe it] — and help me adapt it for my work. Specifically:

1. What would the equivalent input look like in my field?
2. How would I modify the prompt to fit my context?
3. What output would I expect?
4. Write me a ready-to-use prompt that applies this borrowed technique to [a specific task you do].

Step 3 — Test it. Copy the adapted prompt. Use it on a real task. Compare the result to how you'd normally approach it.

Example — a marketer borrowing from investigative journalism:

The technique: Journalists use AI to cross-reference claims across multiple sources and flag inconsistencies.

The adaptation: A marketer uses the same technique to cross-reference their product claims against competitor claims and customer reviews, flagging gaps between promise and reality.

📋 Plan first (Planners start here)

Here's what you're about to do:

1. Pick an unfamiliar field — Choose something genuinely outside your expertise. The discomfort is the point — that's where non-obvious ideas live.
2. Research AI techniques in that field — Use AI to discover how professionals in that domain use AI tools. Look for specific techniques, not generalities.
3. Identify a transferable technique — Pick one that solves a problem similar to something in your work, even though it looks completely different on the surface.
4. Adapt with AI's help — Ask the AI to bridge the gap between the source domain and your domain. Get a ready-to-use prompt.
5. Test the borrowed technique — Apply it to a real task and evaluate whether it gives you a different (and possibly better) result than your usual approach.

"Done" looks like: You have a working prompt borrowed from another field that gives you a new angle on a familiar task.

🧭 Why this matters (Strategists start here)

Most people prompt AI using patterns from their own field — but the most powerful AI techniques are often domain-agnostic. Researchers structure AI analysis differently than marketers, engineers test AI outputs differently than writers, and each field has developed prompting patterns the others rarely see. Cross-domain reframing is how you break out of local optima in your AI usage. At the intermediate level, you'll systematically adapt entire prompt strategies across domains; this exercise builds the muscle of looking outside your field for AI inspiration.

Reflection

• Did the borrowed technique produce a noticeably different result than your usual approach? Better, worse, or just different?
• What made the technique transferable? Was it the structure, the question type, or the underlying problem it solves?
• Which other field would you explore next for AI techniques? What made you choose it?
• 💬 Ask a colleague from a different department how they use AI. You'll likely discover a technique you've never considered — that's cross-domain reframing in action. (Social Learners)

⬆️ Level up

Ready for more? Try CDR-Intermediate-01 — where you'll systematically adapt an entire prompting strategy from an unfamiliar domain.

Back to Cross-Domain Reframing