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Howie Liu

Episode #122

Co-founder & CEO

Airtable

👥Team & Culture🎯Product Strategy🔍User Research

📝Full Transcript

18,134 words
Howie Liu (00:00:00): If you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI native approach? If you can't, then you should find a buyer and then if you really care about this mission, go and start the next carnation of it. Lenny Rachitsky (00:00:12): Or people that work for you, how have you adjusted what you expect of them to help them be successful? Howie Liu (00:00:18): If you want to cancel all your meetings for like a day or for an entire week and just go play around with every AI product you think could be relevant to Airtable, go do it. Lenny Rachitsky (00:00:27): Of the different functions on our product team PM, engineering design, who has had the most success being more productive with these tools? Howie Liu (00:00:33): It really does become more about individual attitude. There's a strong advantage to any of those three roles who can kind of cross over into the other two. As a PM, you need to start looking more like a hybrid PM prototyper, who has some good design sensibilities? Lenny Rachitsky (00:00:49): Do you see one of these roles being more in trouble than others? Today, my guest is Howie Liu. Howie is the co-founder and CEO of Airtable. I'm having a bunch of conversations on this podcast with founders who are reinventing their decade plus old business in this AI era, to help you navigate this existential transition that every company and product is going through right now. Howie and Airtable's journey is an incredible example of this, and there's so much to learn from what Howie shares in this conversation. (00:01:20): We talk about a very interesting trend that I've noticed that Howie is very much an example of, of CEOs almost becoming individual contributors again, getting into the code, building things, leading initiatives themselves. That's something that we call the IC CEO. We also talk about the very specific skills that he believes product managers and pr...

💡 Key Takeaways

  • 1Software companies must be 'refounded' for the AI era; if legacy assets don't provide leverage, consider selling.
  • 2CEOs should return to being 'IC CEOs' (Individual Contributors), acting as Chief Tastemakers by using AI tools hourly.
  • 3Split product teams into 'Fast Thinking' (experimental, shipping weekly) and 'Slow Thinking' (scalable infrastructure) groups.
  • 4In early AI product development, prioritize 'vibes' and open-ended exploration over rigid 'evals' (evaluations).
  • 5The roles of PM, Designer, and Engineer are collapsing; everyone must become a hybrid builder with proficiency in all three areas.

📚Methodologies (3)

👥 Team & Culture

Inspired by Daniel Kahneman's concept, Airtable split its Engineering/Product/Design (EPD) organization into two distinct groups. The 'Fast Thinking' group operates like a startup to ship AI features weekly, while the 'Slow Thinking' group focuses on deliberate, long-term infrastructure and scalability.

Core Principles

  • 1.Fast Group (AI Platform): Operates with high autonomy, ships weekly, focuses on 'wow' factor and top-of-funnel excitement.
  • 2.Slow Group (Core/Infra): Focuses on deliberate planning, scalability (e.g., handling 100M+ records), and reliability.
  • 3.Complementary Growth: Fast thinking attracts new users (top of funnel); Slow thinking retains them and enables enterprise expansion.

"We have the fast thinking group... we want to just ship a bunch of new capabilities on a near weekly basis. And each of them should be truly awesome value."

#'fast#thinking'#structure
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🎯 Product Strategy

A strategic framework for founders to decide how to pivot. It asks leaders to imagine starting from scratch today with AI-native approaches and evaluate if their current assets (codebase, brand, customers) act as leverage or liability.

Core Principles

  • 1.Clean Slate Imagination: If you founded the company today with the same mission, how would you execute using a fully AI-native approach?
  • 2.Asset Valuation: Do your existing building blocks (e.g., no-code primitives) give the AI leverage, or are they legacy debt?
  • 3.The 'Sell' Criterion: If you cannot execute better with your current assets than a new startup could, you should find a buyer and start over.
  • +1 more...

"If you can't... then you should find a buyer and then if you really care about this mission, go and start the next carnation of it."

#refounding#strategy#product
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🔍 User Research

Instead of starting with rigorous evaluations (evals) or metrics, teams should start with open-ended 'play' to develop an intuition for what the model can do. Formal metrics should only be introduced after the product form factor and use cases have stabilized.

Core Principles

  • 1.Mandatory Play: Encourage teams to block out days or weeks just to 'play' with new AI models without a specific deliverable.
  • 2.Vibes Over Evals: In the 0-to-1 phase, rely on human intuition and 'vibes' to judge quality, as AI capabilities are often unknown until tested.
  • 3.Convergent Metrics: Only implement rigorous 'evals' once you have identified the cluster of useful use cases (diverge first, then converge).
  • +1 more...

"For a completely novel product experience or form factor, you should actually not start with evals and you should start with vibes."

#vibes-first#discovery#process
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