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.
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.
Here's what you're about to do:
"Done" looks like: You have a working prompt borrowed from another field that gives you a new angle on a familiar task.
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.
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