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Invest Like the Best with Patrick O'Shaughnessy

Howie Liu - Building Airtable

Tue May 28 2024
TeagasColossus NetworkBest Like the BestMicrosoftAirtableAIbusiness processesno-code approachprimitive functionshuman interface layerinvestment criteriaindustries undergoing changeAI qualityCOVID-19 impactcustomer demanddownsizingfuture of AIsuccessful operators

Description

This episode covers insights from Teagas, Colossus Network, Best Like the Best, Microsoft, Airtable, AI in business processes, no-code approach, primitive functions, human interface layer, Airtable's approach, investment criteria, industries undergoing change, AI quality, Airtable's success, impact of COVID-19, customer demand, downsizing, future of AI, successful operators, and speaker's reflections.

Insights

Teagas offers a comprehensive and rapidly growing transcript library for investment research

Teagas outpaces competitors in content volume and speed.

Founders podcast delves into the lives of legends

The podcast provides insights applicable to work.

In Best Like the Best podcast explores markets, ideas, stories, and strategies

The podcast is focused on better investing time and money.

Airtable's advantage lies in its existing distribution base with Fortune 500 customers

The platform allows customization for various use cases.

Microsoft offers both broad but shallow product experiences and very verticalized solutions

Platforms like Airtable provide horizontally applicable and deep solutions.

The latest generation of LMs are capable of reasoning about advanced topics

AI can be integrated into workflows to automate tasks and improve results in various business processes.

Customization and personalization of software applications are seen as the future

Successful platform companies allow customers to customize their own software implementations.

Primitive functions like collection, search, summary, and synthesis are building blocks for advanced work in AI

Quality of reasoning is seen as a key advancement in AI capabilities.

AirTable uses AI in product operations to capture customer feedback and enhance the product roadmap

The company aims to strike a balance between being a platform and offering application solutions.

Investment criteria for software businesses include having a deep platform foundation and strong integration of AI capabilities throughout the product

The future success of companies may lie in creating platforms with customizable features and extensive AI integration.

Chapters

  1. Teagas, Colossus Network, and Best Like the Best
  2. Microsoft and Airtable: Broad vs Vertical Solutions
  3. AI in Business Processes and No-Code Approach
  4. Primitive Functions and Human Interface Layer
  5. AirTable's Approach and Investment Criteria
  6. Industries Undergoing Change and AI Quality
  7. AI Improvements and Airtable's Success
  8. Airtable's Growth and Impact of COVID-19
  9. Customer Demand and Downsizing
  10. Future of AI and Successful Operators
  11. Speaker's Reflections and Encouragement
Summary
Transcript

Teagas, Colossus Network, and Best Like the Best

00:00 - 06:43

  • Teagas offers a comprehensive and rapidly growing transcript library for investment research, outpacing competitors in content volume and speed.
  • Founders podcast, part of the Colossus Network, delves into the lives of legends to provide insights applicable to work.
  • In Best Like the Best podcast explores markets, ideas, stories, and strategies for better investing time and money.
  • Howie Liu, CEO of Airtable, discusses the platform's focus on intuitive building experiences and integration of AI for productive workflows.
  • Airtable's advantage lies in its existing distribution base with Fortune 500 customers and its platform that allows customization for various use cases.
  • The discussion between horizontal and vertical software solutions in the AI world raises questions about how companies like Microsoft will navigate specificity versus broad usability.

Microsoft and Airtable: Broad vs Vertical Solutions

06:24 - 13:24

  • Microsoft offers both broad but shallow product experiences like the office suite and very verticalized solutions such as Pro-Core in construction.
  • There is a third bucket where platforms like Airtable provide horizontally applicable and deep solutions by giving users building blocks to create specific applications.
  • The latest generation of LMs, like chat GPT, are capable of reasoning about advanced topics, making them broadly and deeply intelligent.
  • Customization and personalization of software applications are seen as the future, with platforms like Salesforce succeeding due to their customizable data schema and flexible platform.
  • Successful platform companies allow customers to customize their own software implementations, moving away from one-size-fits-all solutions.

AI in Business Processes and No-Code Approach

13:01 - 20:01

  • AI can accelerate app development by building use cases based on external understanding of customers.
  • AI can be integrated into workflows to automate tasks and improve results in various business processes.
  • There is potential for trillions of dollars in GDP from leveraging AI models in real business and personal use cases.
  • Behavioral change and enterprise adoption may be key challenges in maximizing the value of AI capabilities.
  • The no-code approach allows non-technical users to experiment with AI-enabled workflows, leveraging advanced models for specific use cases.

Primitive Functions and Human Interface Layer

19:39 - 26:27

  • Primitive functions like collection, search, summary, and synthesis are building blocks for advanced work in AI.
  • LLMs struggle to chain functions together effectively compared to humans in solving real-world problems.
  • Quality of reasoning is seen as a key advancement in AI capabilities.
  • Human interface layer and workflows are crucial for unlocking the economic value of LLMs.
  • Process transformation is more strategically important than standalone AI features for some companies.

AirTable's Approach and Investment Criteria

26:02 - 33:01

  • AirTable uses AI in product operations to capture customer feedback and enhance the product roadmap.
  • The company's founding product philosophy focused on platformizing software into building blocks but evolved to provide more structured templates for customers.
  • AirTable aims to strike a balance between being a platform and offering application solutions, emphasizing flexibility and adaptability in customer engagement.
  • Investment criteria for software businesses include having a deep platform foundation and strong integration of AI capabilities throughout the product.
  • The future success of companies may lie in creating platforms with customizable features and extensive AI integration across various processes.
  • AirTable's approach involves understanding diverse industries and customizing solutions akin to an investor seeking alpha.

Industries Undergoing Change and AI Quality

32:34 - 39:28

  • The speaker views their role as similar to that of an investor, needing to understand different industries and companies for operational changes.
  • Understanding the motivation behind change is crucial for successful software implementation.
  • Digital transformation trends often lack a strategic thesis, leading to wasted investments.
  • Industries undergoing significant change like media, retail, and fin serve are key areas where Airtable focuses due to the need for operational restructuring.
  • Airtable's dominant use cases are in industries experiencing substantial change and in dynamic front office operations.
  • Some businesses, especially in slow-moving industries like restaurants, embrace Airtable due to their innovative and operational mindset.

AI Improvements and Airtable's Success

38:59 - 46:02

  • AI can help users by providing specific use cases and making app development less daunting
  • Improvements in AI quality and consistency can significantly enhance user experience and adoption
  • Market timing and product execution were crucial for Airtable's success in the early stages
  • Organic virality played a key role in demonstrating product-market fit for Airtable

Airtable's Growth and Impact of COVID-19

45:40 - 52:26

  • The company initially faced uncertainty about monetizing their product but saw success with paid plans, reaching milestones of $10,000, then $500k, and eventually $10 million in revenue.
  • Receiving investments led to a shift from being an indie favorite to focusing on mainstream growth and scaling up the team.
  • The impact of COVID-19 caused initial concern for the company due to customer churn from small businesses, leading to raising another round for stability.
  • A surge in demand for collaboration software during the pandemic benefited the company, especially as companies transitioned to remote work and sought structured collaboration tools like Airtable.
  • Meeting the increased demand required scaling up servers, hiring more customer-facing staff, and adapting go-to-market strategies.
  • The challenge now is building foundational structures for sustained growth and managing rapid organizational expansion after experiencing significant headcount growth.

Customer Demand and Downsizing

52:07 - 58:53

  • Customer demand shifted to asking questions about business value before spending
  • Companies optimized their capacity and saw minimal logo churn during the period
  • The company experienced a significant mood shift and focused on building a repeatable go-to-market engine aligned with product vision
  • Tough decision was made to downsize the company despite having a substantial balance sheet to enable continuous hiring and gain external perspectives
  • Smaller organization was believed to enable faster execution in agile ways, emphasizing the importance of tight-knit teams for AI development

Future of AI and Successful Operators

58:37 - 1:05:35

  • Microsoft and Google are top picks due to their roles in AI innovation.
  • New companies will emerge in various industries, led by individuals focused on efficiency and content quality.
  • AI-specific businesses founded by technologists and industry experts will drive innovation.
  • Successful operators combine technology with industry knowledge to leverage AI effectively.
  • Capital allocation is crucial, but attention to detail and agility are key for success at scale.
  • Operators need to be hands-on, involved in team harmony, talent management, and thematic design.

Speaker's Reflections and Encouragement

1:05:19 - 1:09:17

  • The speaker is happy with Airtable but mentions interest in working on non-tech industries like theme parks.
  • The speaker reflects on the kindest things done for them, including support from parents and a personal check from a company founder to extend their runway.
  • Encouragement is given to listeners to build something with Airtable due to its accessibility and potential for growth with AI integration.
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