First Block: Interview with Ivan Zhao and Simon Last, Co-Founders of Notion

Notion’s co-founders trace the company’s rise to a stubborn obsession with craft—paired with a willingness to reset repeatedly until the product’s “taste” finally matched what users needed. In the early years, the team chased a more direct “programming environment” approach for years, then learned that most people don’t want to build software; they want off-the-shelf tools that solve problems quickly. The breakthrough came from disguising that underlying power: shifting Notion from a programming-adjacent tool into a productivity platform, while keeping the same core idea—hide computing power inside everyday document and knowledge workflows.

The path to co-founder-level conviction started with hiring and chemistry. Simon Last, then 20 and fresh out of college, reached out after finding Ivan Zhao’s circle on Twitter and ended up meeting Ivan in person—so quickly that he quit his internship, moved to the Mission area near the early office, and stayed. Ivan credits the decision to bring Simon in to shared thinking about tools, visual programming concepts, and education—plus a sense that Simon’s talent wasn’t yet “Twitter famous,” even if his work was.

As the company searched for product-market fit, the team cycled through multiple rewrites—three or four resets—because their taste ran ahead of their execution. A key lesson was that early-stage expertise often comes with higher standards than the ability to ship, leading to technical and product mistakes that forced a restart. Still, the low points didn’t derail momentum; the founders describe a dynamic where conversations quickly return to the next solvable facet of an enormous problem.

Once Notion began finding traction, customer discovery didn’t come from abstract strategy. The first customers arrived through channels like Product Hunt and then through direct conversations in support and community spaces. The company’s support culture became a research engine: keeping Intercom notifications on, tagging feature requests, and letting engineers read clusters of conversations to understand needs within hours. That approach scaled intuition without building a large dedicated research or product-ops function.

Notion’s product philosophy also stayed deliberately general-purpose without becoming generic. The team built for internal personas—engineers, product, and designers—using flexible primitives (like the “block model”) that could serve multiple functions, while still navigating trade-offs across UX familiarity, UI pixel-level constraints, and what’s technically buildable or real-time. They emphasize that the best system is often the one people already recognize, and that teams need freedom to not ship until the trade-offs that matter most are resolved.

Culture and hiring reinforced the same pattern: “tend the garden” by fixing small confusing issues, keep ownership broad by avoiding rigid code boundaries, and write values down so norms survive growth. Recruiting follows a strict talent-density mindset—if there’s doubt, don’t hire—because each new person is expensive in time and communication.

Finally, the founders position AI as the next “Lego block” primitive for knowledge work. Simon Last describes early skepticism about raw GPT-3, then a turning point as instruction-following improved (with GPT-4) and image models became playful tools. By late 2022, they were already prototyping and pushing the company to invest, arguing that language models can understand information and reshape how people collaborate—making experimentation and empirical testing central as the frontier changes daily.