I think we misunderstand what prompt engineering actually is. It's less about the prompt, and more about how clearly you think. Good prompts should force you to break down messy ideas, name constraints and turn those vibes into concrete steps. If you can explain a problem well to an agent, you've usually already figured out most of the solution. That's why, if you ask me, this skill matters even without AI. It simplifies complexity and makes hard problems feel manageable. The agent just executes. But your choice of vocabulary + style of thinking is your unfair advantage. So, what should a good prompt ideally account for? Here's an excellent example: Build a web app to upload credit card statements (PDF/CSV), auto-categorize spend, detect subscriptions, and show a monthly dashboard. (✓ Clear outcome) Add anomaly detection, budget alerts (80%), and a plain-English AI summary with savings insights. (✓ Defines user value) Ensure secure data handling. Provide schema, APIs, setup steps. Design for multi-card scale. (✓ Controls output + future-proofs)