Your prompts suck. Your AI outputs prove it.

Most developers treat prompt engineering like magic - throw words at the AI and hope for the best. But getting consistent, production-quality results from AI requires actual engineering principles, not creative writing.
This session reveals the systematic approach to prompt engineering that produces reliable results: using AI itself to debug your prompts, building constraint systems that prevent garbage outputs, and creating prompt architectures that scale across your entire development workflow.
You'll master:
- Why "be creative" prompts fail (and the structural patterns that don't)
- How to reverse-engineer successful prompts using AI feedback loops
- Constraint engineering that eliminates 90% of useless AI outputs
- The prompt versioning and testing strategies that actually work in production

Perfect for: Developers integrating AI into workflows, technical writers automating documentation, and anyone tired of playing prompt lottery with inconsistent results.

Live demonstrations: Real prompt debugging sessions, before/after output comparisons, and the systematic refinement process that turns vague requests into precise instructions.

Walk away with: A repeatable prompt engineering framework, debugging techniques that actually work, and the systematic approach to get AI outputs you can actually use.