20Product: Is the Design Phase Dead in a World of AI | Has Claude Code Crushed Anthropic Already | What Roles of a PM Are Less and More Important with AI | How the Best Product Leaders Tell Stories with Noam Lovinsky, CPO @ Superhuman - The Twenty Minute VC Recap
Podcast: The Twenty Minute VC
Published: 2026-01-16
Duration: 46 minutes
Guests: Noam Lovinsky
Summary
Noam Lovinsky, CPO at Superhuman, discusses the evolving role of product management in the age of AI, emphasizing storytelling and the impact of AI on product development cycles. He predicts a future where AI writes the majority of new code and explores the implications for product teams.
What Happened
Noam Lovinsky, CPO at Superhuman, outlines the importance of storytelling in product leadership, stating that the best leaders align market needs with customer demands through compelling narratives. He underscores that effective communication is crucial in shaping product vision and strategy.
Lovinsky argues that the design phase remains vital despite AI advancements, as human creativity and strategic thinking are irreplaceable. He acknowledges that AI tools like Claude Code facilitate coding but emphasizes that they complement rather than replace traditional design processes.
AI is reshaping product development by compressing the exploration phase, allowing for quicker iterations and faster learning cycles. Lovinsky anticipates that within two years, AI will generate 90% of new code at Superhuman, drastically altering team compositions by reducing the need for large engineering teams.
The conversation touches on the potential risks of AI, such as data leakage and prompt injection, viewing these as part of the technology's learning curve. Lovinsky expresses concern over wealth inequality exacerbated by AI, but also notes the potential for AI to create abundance.
Lovinsky predicts significant changes by 2026, including the widespread use of 24-7 AI inference in knowledge work, though he acknowledges current UX limitations might delay this timeline. He also foresees increased public scrutiny and demonization of tech leaders due to job displacement in sectors like law and customer support.
Amid these changes, Lovinsky emphasizes the need for product leaders to focus on platforms that allow customers to build and extend personalized features. Observing user cohorts and understanding their behavior, as demonstrated by YouTube's watch time experiments, remains critical for informed decision-making.
Lovinsky praises Glenn Kelman for his empathetic leadership and ability to communicate market insights effectively. He concludes by expressing a desire for AI to free up time for creativity and innovation, aligning with his passion for building and making things.
Key Insights
- AI is expected to generate 90% of new code at Superhuman within two years, significantly reducing the need for large engineering teams and altering team compositions.
- The design phase in product development remains crucial despite AI advancements, as human creativity and strategic thinking are irreplaceable elements that AI tools complement rather than replace.
- AI's rapid development poses risks such as data leakage and prompt injection, which are considered part of the technology's learning curve, alongside concerns about exacerbating wealth inequality.
- By 2026, the widespread use of 24-7 AI inference in knowledge work is anticipated, though current UX limitations may delay this timeline, with increased public scrutiny and potential demonization of tech leaders due to job displacement.