This presentation outlines techniques for developing advanced AI systems, focusing on common challenges and best practices. We cover the AI Test Driven Product Development Lifecycle (experiment - evaluate - deploy - monitor), emphasizing experimentation with prompting techniques, testing various architectures, and maintaining a model agnostic approach. The presentation also explores the emerging paradigm of Agentic Workflows, detailing components such as planning, execution, refinement, and interface design. Key takeaways include identifying low-risk use cases, iterating on models and prompting techniques, implementing robust evaluation methods, and maintaining quality through continuous monitoring and edge case identification.

Settle back into the days sessions, at Generative AI Summit: Track 1.