AI Startups Need Data Flywheels

When building AI products, the key to sustainable advantage isn't just using the latest models, but creating systems that generate unique data and improve over time.

Data Flywheel Strategy for AI Products

• The models themselves will not be your primary moat - they're becoming increasingly commoditized
• What creates lasting advantage is a combination of:
  • Proprietary data collection - unique information no one else has access to
  • Data flywheels - systems that generate more valuable data through usage
  • Workflow integration - fitting seamlessly into how people actually work

How to build effective data flywheels

• Start with initial proprietary data that gives you an edge
• Design your product to capture valuable user interactions
• Use those interactions to improve your product in ways competitors can't match
• Example: Warp (coding tool) collects data on which code suggestions users accept/reject
  • This creates a feedback loop of increasingly better suggestions
  • Eventually allowed them to launch their own model trained on this proprietary data

Product craft still matters

• The experience layer is critical for adoption and retention
• Products with exceptional craft can overcome distribution advantages of incumbents
• Examples like Granola show that delightful experiences can drive switching behavior
• The best AI products combine both data advantages and exceptional UX

Finding your edge in the AI landscape

• Focus on solving specific vertical problems deeply rather than general capabilities
• Understand workflows intimately - this creates barriers to entry
• Build systems that get smarter with use in ways specific to your domain
• Remember that AI is "malleable" - it gets good at whatever data you train it on

The human element remains essential

• AI is a tool that requires human direction and application
• "AGI is necessary but not sufficient" - it will still require human builders
• The value comes from channeling AI capabilities into solutions people want
• Product builders who understand both the technology and human needs will thrive