Chris Smith: How to think about adding AI to your product

Chris Smith is a longtime engineering leader who has been in the trenches of building with AI & machine learning for years. He’s led the development of data systems & strategies at tech giants like early Google, Yahoo, and Sun; S&P 500's like Live Nation; and a wide variety of startups.—Topics discussed:(00:00) AI industry at inflection point, causing chaos(09:05) Machine learning, neural nets, and generative AI(14:03) Generative AI: LLMs + broad understanding(21:56) Open source models improve specialized problem solving(25:06) Access to data leads to competitive advantage(32:53) AI training improves productivity and learning speed(42:51) Reduced investment in GPT models speeds results(48:47) Expectation mismatch leads to brand perception risks(53:54) Non-technical work is crucial for AI product success(57:30) Building a computer vision product from scratch(01:03:14) A strategic approach to refining and testing prototypes(01:08:04) Closing learning loops—Links & resources mentionedFind the full transcript at: https://podcast.makethingsthatmatter.com/chris-smith-how-to-add-ai-to-product/#transcriptSend episode feedback on Twitter @askotzko , or via emailChris Smith:• LinkedIn• X / Twitter: @xcbsmith• Bluesky @xcbsmith—Related episodes:• #75 Chris Smith: Simple guidelines for AI investment sizing—People & orgs:• Dr. Marily Nika - AI Lead, Meta Reality Lab• Travis Corrigan - Head of Product, Smith.AI—Books:• Evidence Guided - Itamar Gilad—Other resources:• GPT = “generative pre-trained transformer”• Wizard of Oz experiment• Tom Chi - learning loop• Joel Spolsky: The iceberg secret, revealed• ML Ops• Computer vision• Precision-Recall curves• Leaked Google memo: “There is no moat”• Universal basic income (UBI)• Stop-loss order This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit blog.makethingsthatmatter.com