About this webinar
Your team invested in GraphQL for good reasons - faster frontend development, cleaner data fetching, and better developer experience. But as your graph grows and AI initiatives move from experimentation to production, the questions change: How do you secure API access for agentic workflows? How do you maintain visibility across dozens of services? How do you scale without blowing up the on-call pager?
In this session, we'll explore the architectural patterns that separate production-ready graphs from proofs-of-concept. You'll learn how organizations large and small have evolved their GraphQL implementations to handle new use cases - and how they're now extending those same graphs to power AI-driven experiences.
What you'll learn:
The inflection points that signal your graph has outgrown its current setup (and what to do about them)
Governance and security patterns for multi-team graph development
How a well-architected graph becomes the foundation for agentic AI use cases
Real-world lessons from teams running GraphQL at all scales
Whether you're running Apollo Client in production, exploring federation, or evaluating how your API strategy fits into your AI roadmap, this session will give you a practical framework for what comes next.
Meet your speakers
