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:

What would the equivalent input look like in my field?

How would I modify the prompt to fit my context?

What output would I expect?

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:

Pick an unfamiliar field — Choose something genuinely outside your expertise. The discomfort is the point — that’s where non-obvious ideas live.
Research AI techniques in that field — Use AI to discover how professionals in that domain use AI tools. Look for specific techniques, not generalities.
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.
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.
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

What surprised you about the output?
Did the borrowed technique produce a noticeably different result than your usual approach?
What made the technique transferable? Was it the structure, the question type, or something else?
How would you explain what you just did to a colleague?
💬 Discuss: Try explaining your result to someone who hasn’t used AI for this task. What questions do they ask? (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 | 🟢 Basic Level