Talk Overview:
This practical workshop transforms prompt engineering from guesswork into a systematic discipline. You’ll learn the architectural patterns, debugging strategies, and constraint systems that produce reliable, production-quality AI outputs every time.
Key Topics Covered:
The anatomy of production prompts (system messages, context, constraints, delimiters) Core techniques: clarity, Chain-of-Thought, format constraints, and compression Advanced patterns: Tree of Thought, Self-Consistency, ReAct, and meta-prompts Layering techniques for production-ready systems Security and jailbreak resistance strategies Prompt testing, versioning, and iteration workflows
What You’ll Master:
Why vague prompts fail and the structural patterns that succeed Reverse-engineering successful prompts using AI feedback loops Constraint engineering that eliminates 90% of useless outputs Strategic technique combinations for speed, insight, or scale Defensive scaffolding against prompt injection attacks
Who Should Attend:
Developers integrating AI into workflows, technical writers automating documentation, and anyone building systems that require consistent, reliable AI outputs. Level: Intermediate - assumes basic familiarity with LLMs and API integration
