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The Importance of Machine Learning in AI
Stripe has been employing a lot of machine learning techniques there again for years. And we couldn't operate the company without them. Most of the AI on these is running on Stripe and we're working very hard to make sure we serve all their needs. We started working with open AI when they had the data that was a kind of private beta of GPT for available at the beginning of this year.
Brought to you by Mixpanel—Product analytics that everyone can trust, use, and afford | Eppo—Run reliable, impactful experiments | Braintrust—For when you needed talent, yesterday
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David Singleton is Chief Technology Officer at Stripe, where he oversees engineering and design teams. Since joining Stripe, David has helped grow the technology org across the U.S. and developed new engineering hubs in Singapore and Dublin as well as Stripe’s fifth hub, remote engineering, across the globe. Before Stripe, he spent 11 years at Google, where he was VP of Engineering, leading product development and coordinating more than 15 different hardware partnerships. In today’s episode, we cover:
• Hiring secrets that set Stripe employees apart
• How to build a product-minded engineering team
• How to operationalize meticulousness
• Strategies for maintaining developer productivity at scale
• The process of “friction logging” used to make better products
• How AI is changing the way engineers work
• Insights for planning and prioritizing at scale
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Find the full transcript at: https://www.lennysnewsletter.com/p/building-a-culture-of-excellence
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Where to find David Singleton:
• Twitter: https://twitter.com/dps
• LinkedIn: https://www.linkedin.com/in/davidpsingleton/
• Website: https://blog.singleton.io/
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Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• Twitter: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
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In this episode, we cover:
(00:00) David’s background
(04:22) How Stripe’s unique hiring process has helped them build an incredible team
(12:27) An example of a relentlessly curious and passionate employee
(14:11) Structured hiring loops at Stripe
(16:39) How Stripe built a product-minded engineering culture
(21:56) Stripe’s operating principles
(25:39) How Stripe uses “friction logging” to build a meticulous product culture
(32:22) How to operationalize friction logging
(35:02) How to set PMs up for success
(36:53) Stripe’s collaborative approach to product evaluation
(41:17) Advice for presenting to CTOs
(42:58) How to get better at building products
(45:28) Stripe’s “engineerications” and the importance of getting into the weeds as a leader
(52:03) Auto-testing and other strategies to improve shipping speeds
(59:29) Improving developer productivity
(1:00:54) How AI has impacted the way Stripe builds product
(1:07:03) Why David is excited about Copilot
(1:09:24) Lessons from managing people
(1:14:30) Planning and prioritization based on first-principles thinking
(1:18:23) Lenny’s feedback from using Stripe
(1:19:14) What’s next for Stripe
(1:22:10) Lightning round
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Referenced:
• Stripe: https://stripe.com/
• Jeff Weinstein: https://www.linkedin.com/in/jeffwweinstein/
• How we use friction logs to improve products at Stripe: https://dev.to/stripe/how-we-use-friction-logs-to-improve-products-at-stripe-i6p
• GitHub Copilot: https://github.com/features/copilot
• High Output Management by Andrew Grove: https://www.amazon.com/High-Output-Management-Andrew-Grove/dp/0679762884
• Build by Tony Fadell: https://www.amazon.com/Build/dp/1787634116/ref=tmm_pap_swatch_0
• Scaling People: Tactics for Management and Company Building by Claire Hughes Johnson: https://www.amazon.com/Scaling-People-Tactics-Management-Building/dp/1953953212/
• Andrej Karpathy on YouTube: https://www.youtube.com/@AndrejKarpathy
• Midjourney: https://www.midjourney.com/home/
• Emily Sands: https://www.linkedin.com/in/egsands/
• Michelle Bu: https://www.linkedin.com/in/michellebu/
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
Lenny may be an investor in the companies discussed.
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