Laura Alber describes a build process that leaned on existing data and narrow, focused outcomes. The team “built this entire experience in under 30 days,” she said, and could not have matched that pace with a custom stack.
The platform handled orchestration and guardrails while Williams Sonoma brought recipes, service knowledge, and product feeds.
That speed matters because most AI programs stall inside enterprises. They stall because of data access, unclear ownership, legal reviews with no clock, and change-management processes that starts after launch rather than before.
Williams Sonoma cut through by giving agents a clear remit, by training on years of service logs, and by letting agents help test other agents.
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