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Timestamps are as accurate as they can be but may be slightly off. We encourage you to listen to the full context.
Grant Lee, co-founder of Gamma, shares the extraordinary journey of building a $2 billion AI presentation tool that reached $100 million ARR in just over two years with only 30 employees. The episode explores how Gamma achieved profitability early on and grew sustainably without raising significant funding initially. (07:00) Grant recounts receiving one of the harshest investor rejections, being told his idea was "the dumbest idea" the investor had ever heard, which ultimately motivated him to prioritize growth from day one. The conversation dives deep into how they found product-market fit by completely reimagining their onboarding experience, focusing obsessively on making the first 30 seconds magical. (11:09)
Grant Lee is the co-founder and CEO of Gamma, the AI-powered presentation and website design tool valued at over $2 billion. Previously, he was COO at a startup and worked in consulting, which gave him firsthand experience with the presentation creation pain points that inspired Gamma. He's an angel investor in several companies including Voice Panel and is known for his founder-led marketing approach and lean team philosophy.
Lenny Rachitsky is the host of Lenny's Podcast and author of Lenny's Newsletter, one of the most popular publications for product managers and growth professionals. He previously worked at Airbnb as a Senior Product Manager and is known for his deep dives into product-market fit, growth strategies, and startup operations.
After launching successfully on Product Hunt but seeing growth plateau, Gamma made a bet-the-company decision to rebuild their entire onboarding experience. (11:09) They focused all hands on making the first 30 seconds of the product feel magical, ensuring users would tell their friends about it. This approach treats new users as "selfish, vain, and lazy" - you must earn each subsequent 30 seconds of their attention. The result was explosive growth from hundreds to tens of thousands of daily signups purely through word-of-mouth. This demonstrates that true product-market fit isn't just about user acquisition, but about creating a "word-of-mouth machine" where organic growth becomes your primary engine.
Grant emphasizes that founder-led marketing goes beyond just posting on social media - it's about controlling the narrative and breaking through noise strategically. (24:14) His viral tweet announcing Gamma's AI features was intentionally "provocative" and "click-baity," designed to generate engagement and controversy. The key is developing copywriting skills, understanding what makes content shareable, and being willing to do things that feel uncomfortable. Founders should invest time weekly in creating content, testing different approaches across platforms (LinkedIn vs Twitter require different strategies), and building goodwill through valuable content that can later be exchanged for product promotion.
Rather than partnering with large influencers, Gamma found success working with thousands of micro-influencers (educators, consultants) who genuinely used and benefited from the product. (42:15) Grant personally onboarded every early influencer, spending time on calls to ensure they understood the product deeply and could tell Gamma's story in their own voice. This approach creates authentic advocacy within "echo chambers" where recommendations carry significant trust. The strategy requires casting a wide net since only 10% of influencers will drive 90% of reach, but the investment in relationship-building and authentic usage creates sustainable word-of-mouth amplification that traditional advertising cannot match.
Gamma developed a system where they could have an idea in the morning, build a functional prototype, recruit real prospective users through platforms like Voice Panel, and gather feedback by evening. (65:04) This approach involves finding people with "zero skin in the game" who fit the target persona but have no emotional investment in the product's success. By watching these users struggle with the product and hearing their real-time thoughts, the team could identify pain points immediately and iterate rapidly. This methodology prevents months of building features nobody wants and creates a continuous feedback loop that informs product development decisions with real user behavior rather than assumptions.
Coming from Optimizely, Grant built experimentation mindset into Gamma's DNA from day one, allowing them to test across 20+ AI models simultaneously and optimize for both user value and unit economics. (76:54) This approach enabled them to maintain profitability while scaling, as they could continuously optimize their AI model usage for different tasks - using specialized models for outlines, visuals, or content editing rather than applying expensive models universally. The experimentation framework extends beyond product features to pricing, messaging, and growth tactics, creating a data-driven culture that makes better decisions faster than competitors who rely on intuition alone.