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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.
In this episode of This Week in Startups, Jason Calacanis joins from Riyadh, Saudi Arabia, where he's running Founder University, alongside venture capital heavyweights Deedy Das from Menlo Ventures and Jay Eum from GFT Ventures. The panel dives deep into the shocking scale of AI company fundraising, the recent leadership transition at Sequoia Capital with Roelof Botha stepping back, and how the venture landscape has fundamentally shifted toward revenue-focused investments. (03:37)
Jason is the founder and host of This Week in Startups and runs Launch, an investment company and accelerator. He's a veteran angel investor who was part of Sequoia's original scouts program and has invested in companies like Uber through early seed funds.
Deedy is a newly promoted partner at Menlo Ventures who joined the firm without traditional venture experience. He previously worked at a startup called Glean that achieved significant success, reaching over $100 million ARR, and is known for his active presence on social media analyzing venture trends.
Jay is co-founder of GFT (Global Frontier Technology) Ventures, a frontier tech fund focused on AI and data science companies. He has over 20 years of experience in venture capital and previously worked in corporate venture at Samsung and NVIDIA before launching his current fund in 2021.
The venture landscape has dramatically shifted toward companies with proven revenue rather than just promising concepts. (44:41) Jay explains that investors now have the luxury of choosing between companies that have already validated product-market fit with real revenue, rather than taking risks on pre-revenue opportunities. This represents a fundamental change from previous eras when VCs would invest in founders with just an idea and a deck. The bar for pre-seed has risen substantially, with many funds now expecting companies to show meaningful traction before investment.
One of the biggest mistakes new VCs make is deploying all their capital during peak valuation periods. (55:33) Jason emphasizes learning from veteran investors like Roelof Botha and Doug Leone who taught him to deploy funds over 3-4 years rather than 18 months. This time diversification protects against being caught in valuation bubbles and ensures you're not making all investments at market peaks. Successful venture investing requires patience and disciplined deployment timing, not rushing to put capital to work.
The growth rates of AI companies are unprecedented in startup history. (32:04) Jay notes he's "never seen anything like it in twenty years," with companies like Anthropic growing from $1 billion to potentially $10 billion ARR in a single year. This acceleration is possible because AI companies are building on decades of existing infrastructure - connectivity, mobile distribution, cloud computing - while benefiting from customers already trained to pay for software services. The combination of ready infrastructure and willing enterprise customers creates unprecedented scaling opportunities.
In the AI era, if you can be a product-led growth company, you absolutely must be one. (78:44) Deedy emphasizes that AI companies going enterprise-first will be "steamrolled" by those with massive consumer awareness and product-led growth. Companies like OpenRouter succeeded because they built awareness through product-led growth rather than traditional B2B enterprise sales. The key is creating a product that users can discover, try, and adopt organically, which then creates natural enterprise demand.
Rather than building broad horizontal solutions, successful startups focus intensely on specific use cases or verticals. (80:27) Jason highlights NextVisit AI, which specifically targets psychiatry note-taking rather than general clinical notes. This laser focus allows startups to perfect their solution for a specific customer need, achieving such high quality that customers become delighted advocates. The principle: "Do one thing better than everybody in the world" rather than trying to be everything to everyone.