.bolt.new is the second fastest-growing product in history—only behind ChatGPT. They hit $20M ARR just 60 days after launching the product, and ~$40M ARR (and 1 million DAU) just five months in 🤯 The craziest part is that they almost shut down the company. After seven years of building... and iterating, they weren't getting anywhere. It turned out that what they'd been building was exactly what you need to build AI apps in the browser at scale. So they decided to give it one last shot. An overnight success, seven years in the making. In my conversation with Eric Simons (founder and CEO), we discuss: 🔸 Why Anthropic’s 3.5 Sonnet model was the critical breakthrough that made AI-generated code production-ready and unlocked the entire text-to-app market 🔸 How Bolt leverages WebContainer technology—a browser-based operating system developed over seven years—to create a dramatically faster, more reliable AI coding experience than competitors 🔸 How Bolt reached nearly $40M ARR and 3 million registered users in just five months with a team of only 15 to 20 people 🔸 Why PMs may be better positioned than engineers in the AI era 🔸 How AI will dramatically reshape company org charts 🔸 Why Eric lived at AOL’s HQ for many months 🔸 Much more Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 @Get_Eppo — Run reliable, impactful experiments: 🏆 Fundrise Flagship Fund — Invest in $1.1 billion of real estate: 🏆 OneSchema — Import CSV data 10x faster:show more

Some key takeaways: 1. Bolt succeeded by doing what was thought impossible—running full dev environments in a browser. 2. Bolt operated on minimal resources and near-zero runway, mostly just staying alive long enough to keep trying new things. When Claude 3.5 Sonnet launched, it changed everything. 3. The nature of coding teams is shifting. PMs and designers can now produce high-fidelity prototypes—and even complete apps—on their own, requiring fewer engineering resources for frontend tasks. 4. Lessons from Bolt’s startup story: a. Deep technology investments can take years to find product-market fit. b. Keep burn rates extremely low to maximize runway for experimentation. c. Small teams with high context per person can outperform larger organizations. d. Daily all-hands meetings create zero fidelity loss in communication. e. Surviving long enough to catch market timing can transform a struggling startup. 5. AI’s organizational implications for companies: a. Projects that cost $30,000 can now be built for $300. b. Development timelines are reduced from months to days or hours. c. Product managers can directly implement their vision without engineers. d. Entrepreneurs can launch functional businesses without technical co-founders. e. Fewer frontend engineers are needed per product team. f. Design-to-code workflows will become seamless and instantaneous. g. Small, high-context teams can move dramatically faster than larger organizations.

Longevity isn’t just for billionaires. Julie Gibson Clark spends less than $100 monthly and outranked the wealthiest on the longevity leaderboard. Her secret? NOVOS Core. Affordable choices, big impact. Read her story here:

@boltdotnew @ericsimons40 and team are legends! Great episode

@boltdotnew just been watching this Best. Lenny. Podcast. Ever!! amazingly candid interview

@boltdotnew I've been waiting for this podcast! Awesome work

@boltdotnew Do these companies claiming this ARR actually provide evidence?

@boltdotnew It would be pretty crazy and fairly unprecedented if they were lying.