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Fast, Flexible, and Federated: How Wayfair’s Schema-Driven UI Supercharges Experimentation

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Wayfair describes a schema-first CMS called BlockBuilder CMS that mixes server-driven UI with the Apollo federated graph to deliver configurable blocks, reusable product cards, and first-class ties into personalization and experimentation. The system runs 500+ block types, handles ~2B requests/day, sees P50 ≈ 5ms and P99 < 60ms, and supports 600 internal CMS users and ~1,000 developers across storefronts. Demoed flows show AI-assisted page generation, CI-backed schema publishing, experiment creation, and successful production rollout.

AI-written summary · about

  1. 0:00Block Builder intro at Wayfair
  2. 1:04Agenda overview
  3. 1:45Wayfair’s mission and challenges
  4. 3:10Legacy monolith and UI benefits
  5. 4:34Schema-driven UI concepts
  6. 6:42Introducing Block Builder demo
  7. 7:22Live demo: homepage config
  8. 8:26SEO landing page with AI
  9. 9:50Editing composable page blocks
  10. 10:53Unified product cards and components
  11. 12:43Self-service and integrations
  12. 13:25Block Builder architecture overview
  13. 14:07Scalability and performance metrics
  14. 14:48Deep dive: Block Builder architecture
  15. 15:49Content management layers
  16. 17:14Schema-first UI generation
  17. 17:56Content delivery patterns
  18. 19:19Dynamic data dependencies
  19. 21:30Schema to experimentation flow
  20. 24:58Creating experiments in Block Builder
  21. 27:11Results and impact on Wayfair
  22. 27:33Two years of experimentation velocity
  23. 29:20Key learnings from Block Builder
  24. 30:03Adoption and platform philosophy
  25. 31:30Flexibility and governance design
  26. 32:11Reliability and SLOs prioritization
  27. 32:34Q&A
  28. 33:15Server-side rendering and queries
  29. 34:18Reusable components and support
  30. 35:41SSR strategies and plans
  31. 36:23CMS comparison and open-source
  32. 37:27Reducing experimentation friction
  33. 38:50Engineering feedback and adoption
  34. 39:54Client teams’ experience
  35. 41:21Schema complexity and payload size
  36. 42:46Handling data dependency failures
  37. 44:53Closing remarks
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