Fund/Build/Scale

Walter Thompson

After working for years in early-stage startups and as a journalist, here are three hard truths I’ve learned:1. Success in Silicon Valley hinges on connections, hard work and luck.2. Startups often fail because founders lack fundamental business knowledge.3. Real, actionable advice comes from those who’ve actually done it.There’s no such thing as “founder DNA.” If you’re willing to take on risk and invest years of your life in something that has maybe a 10% chance of paying off — less if you’re a woman or person of color — you can be a startup founder.Here’s why I founded Fund/Build/Scale:1. To help founders make fewer mistakes.2. To share successful strategies that can accelerate your go-to-market journey.3. To inspire more people to see themselves as potential founders. There’s a lot of overlooked talent out there, and we are missing out.This podcast is for anyone who’s interested in learning the basic skills required to launch a startup, secure initial funding and transform

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Эпизоды

137 эпизодов

  1. Do the Work Before You Start the Clock 44:19
  2. What You Permit Is What Gets Produced 49:56
  3. How VCs Judge Founders With No Track Record 39:40
  4. How to Know If Your Startup Idea Is Worth Pursuing 36:19
  5. Why Technical Founders Hire Marketing Too Late 41:29
  6. CVC Is Not Your Exit Strategy or GTM Plan 36:13
  7. AI Makes Building Easier. Selling Is Still Hard. 41:43
  8. The Most Expensive Money You'll Ever Raise 35:13
  9. Money Is the Only Customer Validation That Matters 49:06
  10. What Hospitals Are Actually Buying in the AI Boom 38:35
  11. Your First Marketing Hire Is Probably Not a CMO 45:19
  12. How AI-Native Startups Actually Get Built 51:33
  13. Why Great Founders Are “Angry at the Problem” 56:28
  14. Turning Utility Into Habit: Beyond Basic Gamification 37:20
  15. Selling Unproven AI to Skeptical Enterprise Buyers 31:28
  16. From Seed to Growth: What African Founders Need to Know 46:36
  17. What Investors Actually Look For in the First 18 Months 50:28
  18. Is the Defensible Moat a Myth in AI? 56:44