From Prompt Engineering to Enterprise AI: Building Scalable, Governed AI Products
About this session
As organizations move from AI experimentation to enterprise-wide adoption, prompt engineering must evolve into a disciplined capability supported by governance, strategy, and scalable operating models. This session explores how structured prompting can be transformed into an enterprise AI development framework that enables teams to build, deploy, and scale AI solutions responsibly.
Using real-world examples—including an AI-powered Career Path GPT and a production-ready mobile application built with Lovable and Supabase—the session demonstrates how prompt engineering extends beyond conversations to drive product architecture, development, testing, and release management. It also covers prompt versioning, context engineering, guarded AI playgrounds, governance controls, ethical AI principles, mandatory user acknowledgements and disclaimers, analytics-driven insights, and enterprise release processes that ensure AI solutions are secure, compliant, and production-ready.
Attendees will gain a practical blueprint for moving from individual AI use cases to an organization-wide AI strategy that balances innovation with governance and enables responsible AI adoption at scale.
Speaker
Key takeaways
- Learn when and how to apply different prompting techniques across the AI product development lifecycle.
- Understand how to build and operationalize an enterprise AI strategy with governance, guardrails, analytics, and scalable release processes.
- Discover how to build innovative AI applications within governed environments that encourage creativity while ensuring security, compliance, and responsible AI practices.