Editing Cross-Domain Reframing (section)

== What this looks like at each level ==

=== Basic — Borrowing a technique ===

You're learning to look outside your own field for AI inspiration. The core skill: taking a specific AI technique from an unfamiliar domain and adapting it for your own work.

'''What it feels like:''' You discover that data scientists use a particular prompt structure for analysis, adapt it for your project management work, and get a result that's noticeably different from your usual approach. The "stolen technique" reveals that your prompt habits had been constrained by your field's conventions.

=== Intermediate — Transplanting a framework ===

You've moved from borrowing a single technique to systematically transplanting an entire problem-solving framework. You map each step of the foreign framework to your context, noting where the mapping is direct, where it needs modification, and where it breaks down entirely.

'''What it feels like:''' You take a decision-making framework from military strategy (or medicine, or game design) and apply it to a challenge in your work. The parts where the mapping breaks down teach you more about your problem than the parts where it works smoothly.

=== Advanced — Building a transfer library ===

You're systematically collecting, testing, and documenting transferable AI techniques from multiple fields. You build a personal prompt library with tested adaptations, transfer notes, and usage guidance — a resource that compounds over time and becomes shareable.

'''What it feels like:''' You have a documented library of 5+ prompt patterns borrowed from other fields. You can articulate ''why'' a technique transfers, not just that it does. Colleagues start asking you for non-obvious approaches to their AI challenges.