Agent Returns $4.21M Net Revenue With No Definitions: Hamel Husain's 11 Lessons for AI Products
hugobowne · x · 2026-09-04
Hugo Bowne shares 11 lessons from Hamel Husain on building AI products in the age of agents. Opening case: a data-analysis agent returned $4.21M in net revenue without showing the definition, tables, filters, joins, dates or fiscal calendar — "what the hell is net revenue?" highlights the black-box problem. Themes: inspect traces before writing evals, product design determines the eval signals you collect, labels should teach the agent what to surface next, and data-science judgment matters more than ever.
Related event: Hamel Husain: Don't Build AI Products If You Won't Inspect Your Own Data(12 posts)→
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