Sponsored Session: GraphQLs Future is Rooted in Governance
summary
Argues that GraphQL becomes enterprise-ready by turning schemas into metadata-driven outputs and favoring configuration over code, then demos it: a six-command script introspects a Postgres source, generates rich metadata, compiles an executable GraphQL schema, and feeds that context to LLMs (ChatGPT/Claude) to produce accurate natural-language queries. Notes metadata can be 10–100x larger than payloads and cites a 25M-person Australian study. Result: autogenerated schemas and LLM queries work far better when metadata is present.
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chapters (7)
- 0:00Introduction and background
- 2:49GraphQL’s maturity curve
- 7:02What is governance?
- 10:30Metadata’s role in governance
- 13:58Semantic data layer concept
- 19:09Demo of metadata-driven GraphQL
- 24:45Future of GraphQL and Q&A
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