Podcast Notes Playlist: Startup

Full Ratchet: 161. Why SaaS is not a fit for VC and How AI Compounds Competitive Advantage (Ash Fontana)


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Podcast Notes Key Takeaways
  • Most VC firms are not “focused funds” – they’re more general (they invest in a wide range of companies across many different fields). This is different from Zetta – they only invest in AI & machine learning companies.
    • Focused funds get a 16% higher multiple on invested capital and a 33% higher ROI compared to generalist funds 
  • The 4 Phases of AI:
    • Phase 1 (low risk): AI applied to consumer applications
      • Ex. – Google and Amazon giving recommendations
    • Phase 2 (slightly higher risk): AI applied to enterprise SaaS companies
      • Ex. – CRMs suggesting leads
    • Phase 3 (high financial risk): AI-centric applications that completely replace a workflow
      • Ex. – Using AI tech to estimate damage on a car, computer vision in autonomous cars, etc.
      • We are currently in Phase 3
      • The key metric for phase 3 AI: Is the efficacy better than a human?
    • Phase 4: (very high financial risk): Applications we haven’t considered before
      • Ex. – Using AI to optimize data center use or energy flow across an electricity grid, making medical diagnoses, etc.
    • Note – In many cases, even if an AI tech has better efficacy than it’s human counterpart, it will still incur adoption risk. Many people are not ready to trust AI as a total replacement for human judgment.
  • AI itself shouldn’t be feared. However, AI can create monopolistic power held by a few companies– this is something to be concerned about.


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Ash Fontana of Zetta Venture Partners joins Nick to discuss Why SaaS is not a fit for VC and How AI Compounds Competitive Advantage. In this episode, we cover:

  • Categories of AI that Ash is most interested in
  • The difference between real AI and AI-enabled companies
  • Why SaaS will cease to be investable by VCs
  • The current AI stage of adoption
  • How he times the market
  • The four phases of AI
  • What phase of AI they invest in
  • How AI is and will be affected by limited data
  • How startups can compete for talent w/ GAFA (Google, Amazon, Facebook, Apple)
  • The moats being created by their AI-first portcos
  • How they think about metrics and milestones for AI-backed companies
  • If AI should be feared
  • and finally we wrap up w/ Ash's thoughts on Chris Dixon's position that we will see a movement from centralization back to decentralization in tech-- and the role that AI will play

 

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