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The Problem Solvers: Kay Zhu at Genspark

Kay Zhu built Genspark on a belief he's living at home: that AI should free people to follow their heart. His teenage son is studying commercial dance instead of computer science with his full support. As CTO and co-founder, Kay built Genspark to make that possible at scale with an all-in-one AI workspace for business. In a market moving this fast, anyone can build, but Kay believes the team is what makes the difference. He chose Claude for its reasoning capabilities, and found something beyond the model: a close partnership with Anthropic that let him take Genspark further than he could alone. The Problem Solvers is a series from Anthropic speaking to founders about how they're solving problems, and why they build with Claude. Learn more about how Kay Zhu is building with Claude: https://claude.com/customers/genspark Discover more from the founders building at the frontier: https://claude.com/problem-solvers

Kay Zhuguest
May 22, 20262mWatch on YouTube ↗

CHAPTERS

  1. AI changes what’s “safe” to study: following your heart

    Kay Zhu reflects on how AI is reshaping career planning and education choices. She shares a personal example—shifting from pushing computer science to supporting her son’s passion for commercial dance—because AI expands what people can do regardless of major.

  2. What Genspark is building: an all-in-one AI workspace for white-collar work

    Kay explains Genspark’s product vision as a unified AI-powered workspace aimed at everyday knowledge workers. The platform focuses on embedding AI directly into common productivity artifacts rather than being a standalone tool.

  3. Receiving new model requests: curiosity as a company reflex

    When the Applied AI team sends something new, Kay describes it as exciting rather than burdensome. The engineering team’s curiosity about the latest model advances turns new requests into moments of momentum.

  4. Why partnerships matter for a small startup

    Kay emphasizes that being a small team makes it impossible to do everything in-house. Trusted partners help Genspark move faster and de-risk exploration, especially in a fast-evolving AI landscape.

  5. Rethinking moats: speed of change undermines traditional defensibility

    Kay pushes back on the idea that companies can rely on classic moats in today’s AI environment. Because capabilities shift quickly, she argues durable advantage is harder to sustain through technology alone.

  6. The real moat: culture of exploration and fast execution

    For Kay, the only lasting defensibility is team culture—especially a bias toward trying the newest technology and executing quickly. This culture enables continuous adaptation as the tools and models evolve.

  7. Openness in collaboration: secrecy depreciates quickly

    Kay argues that in AI, holding secrets too tightly is often counterproductive because knowledge becomes obsolete fast. Openness enables better collaboration outcomes and faster shared learning.

  8. Trust and tight feedback loops: what makes partnerships work

    Successful partnerships, Kay says, rely on deep mutual trust paired with rapid feedback. When collaboration is working well, communication becomes frequent and iterative, enabling quick adjustments.

  9. Embracing uncertainty: Genspark’s future will feel like magic

    Kay closes by describing the unpredictability of where Genspark will be in two years. She frames uncertainty as a feature of the moment—expecting rapid breakthroughs that will seem almost magical in hindsight.

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