Framework
Distribution Before Idea
In an era when building costs approach zero, idea originality is no longer the primary differentiating variable. Who is launching matters more than what is launching — distribution, credibility, and persona-fit are the new moats.
How it works
- 1The cost structure shift: when AI collapses the cost and time to build, a thousand people can ship the same app. The scarce input is no longer engineering skill — it's the ability to get the product in front of a paying customer first.
- 2Persona-fit as moat: a personal trainer with an existing following is the right person to launch a fitness app, regardless of competitive saturation. Their audience trusts them before the app exists.
- 3The Cal.ai example: launched before the vision AI was accurate, grew distribution while the models improved. By the time competitors arrived with better tech, Cal.ai had compounding distribution advantages those competitors couldn't buy.
- 4Greg Eisenberg's framework: audience → community → product. Build the audience first, let it self-select into a community with shared identity and recurring pain, then build the product that solves that community's specific problem.
- 5Practical implication: the first question isn't 'what should I build?' It's 'who do I already serve, and what problem do they already have?' Distribution is the lead input; product is the output.
Hear it on the podcast
AI That Turns Ideas Into Real CompaniesListen to the episodeMore from this episode
Build Backwards from Business RequirementsWoz's core development philosophy: architecture decisions, security guardrails, and compliance requirements are defined at the start from a CTO lens — not added iteratively after prototyping proves the concept.AI-Augmented EngineeringUsing AI to accelerate boilerplate and pattern-matching while maintaining full human architectural ownership — every line committed is understood and owned by a developer. The opposite of vibe coding at production quality.
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