Keynote: GraphQL in the AI Era
summary
Argues that GraphQL already underpins enterprise AI work at retailers, hospitality, and health care and must become the standard for the new context graph, citing Opus 4.5/Claude-style agents and Apollo experiments that connect agents to an applicant tracking system while enforcing field-level security. Claims GraphQL’s declarative fields cut LLM input by 80–95% token reduction, touts built-in introspection for discovery and performance, and calls for tight cooperation with MCP tooling.
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chapters (10)
- 0:00Introduction and AI-GraphQL link
- 1:24Agents as enterprise priority
- 3:10Enterprise silos and agent challenges
- 6:23Context graph necessity
- 8:28Cost control with GraphQL
- 9:29Safety and field-level security
- 10:32Performance and schema introspection
- 11:36GraphQL as core language
- 12:17Evolving GraphQL for AI
- 13:22Join MCP ecosystem
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