WhoBuilt

Will OpenAI Kill All Startups?

Jul 13, 2023· 13 min· 143K views·Watch on YouTube

Speakers

Michael Seibel and Dalton Caldwell of Y Combinator discuss whether OpenAI will eliminate startup opportunities and what founders can learn from earlier technology shifts.

Keep the AGI debate in scope

Seibel and Caldwell say their discussion is about practical effects on startups, not whether or when AGI will arrive. They point founders to history as a way to reason about technological change without speculating about scenarios they cannot assess.

Use AI to improve the product

Caldwell says major shifts such as farming, electricity and the internet enabled more businesses and often gave startups an advantage over incumbents. He and Seibel distinguish useful AI features that improve retention, product quality or customers’ willingness to pay from adding AI mainly to attract investors.

Look for builders with a reason to start now

They describe two groups drawn to the moment: domain experts who see a chance to apply their AI knowledge, and newcomers eager to learn while the tools are still unfamiliar to many. They compare this energy to early mobile app development and the arrival of cloud computing.

Search for second-order opportunities

Seibel says OpenAI may handle many obvious, low-hanging-fruit ideas, while less obvious products could emerge from what LLMs make possible. He uses Uber, enabled by the iPhone, to illustrate how a platform can lead to businesses beyond its most apparent uses. He argues that a product starting as a simple wrapper can grow if customers value it.

Build for customers, not the hype cycle

Seibel advises founders not to copy AI superficially just because it is fashionable, but to use available tools to solve real customer problems. He argues that companies focused on building AGI may leave room for others to improve people’s lives and businesses with existing AI tools.

Takeaways

  • Use AI where it measurably improves customer outcomes, retention or product quality.
  • Treat a basic AI product as a possible starting point; test whether customers want its next version.
  • Look for problems newly solvable with current tools, including consequences beyond the obvious use cases.
  • Use domain expertise or deliberate hands-on learning to find opportunities others may overlook.
  • Build for customer needs rather than adding AI mainly to raise money.

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