Chris Smith: How to think about adding AI to your product Make Things That Matter

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.
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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
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Links & resources mentioned
Find the full transcript at: https://podcast.makethingsthatmatter.com/chris-smith-how-to-add-ai-to-product/#transcript
Send episode feedback on Twitter @askotzko , or via email
Chris Smith:
• LinkedIn
• X / Twitter: @xcbsmith
• Bluesky @xcbsmith
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Related episodes:
• #75 Chris Smith: Simple guidelines for AI investment sizing
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People & orgs:
• Dr. Marily Nika - AI Lead, Meta Reality Lab
• Travis Corrigan - Head of Product, Smith.AI
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Books:
• Evidence Guided - Itamar Gilad
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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


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