Trial and error can only get you so far when working with generative AI, because when you're running a prompt hundreds or thousands of times a day, you need to know when and why it fails. Prompt engineering isn't about finding the right combination of magic words that tricks the AI to do what you want, it's a process for building a production-grade AI system that delivers the results you need, reliably and at scale. We'll apply prompt engineering principles to a real-world AI use-case and make the strategic trade-offs needed to make your AI products economically viable. If you have tried prompting to automate a task, but couldn't get good enough results, this talk will give you actionable steps for closing that gap. You'll take away a checklist for optimizing prompts from idea to production, using principles that are transferable across models and modalities.