February 21, 2026

AI Prototyping: From Static Screens to Live MVPs

42 minutes

In this episode, host Michael Bernzweig talks with Ricardo Tosatto, CEO at Esfera and COO at Esfera Studio, about how AI is changing product design and prototyping. Ricardo explains why traditional design teams spend 70–80% of their time inside tools like Figma and still end up with static prototypes that don’t reflect real user behavior. He shares how AI‑powered tools can generate working UI, flows, and states so teams can test multiple functional MVPs quickly, get better feedback, and free designers to focus on customer insight, problem‑solving, and strategy.

00:00 – Introducing Ricardo Tosatto and the future of prototyping with AI

00:50 – Ricardo's background and journey into tech and product management

02:30 – The evolution of design tools from Figma to AI-enabled prototypes

04:00 – Why static prototypes can hinder real product validation

06:00 – The role of AI in automating asset creation and speed to market

08:15 – Risks of relying solely on static or non-functional prototypes

10:30 – Bridging the gap between design and development with AI

12:45 – Reimagining the role of designers in an AI-powered landscape

15:00 – How rapid prototyping accelerates user feedback and product-market fit

17:20 – Choosing the right tools and workflows for functional MVPs

19:30 – First steps for startups to implement AI-driven prototyping

21:45 – Common pitfalls in early product development and how to avoid them

23:55 – The importance of testing and iteration cadence in CRO and UX

26:10 – Leveraging AI for HR data unification and employee insights

28:30 – Building trust with leadership through data and quick wins

30:50 – Deciding which growth levers to test first in enterprise settings

33:00 – Adjusting experimentation based on traffic volume and niche markets

35:15 – Practical tips for mid-market companies to unify HR systems

37:40 – The importance of a phased approach for data integration

39:10 – Maintaining a continuous testing and learning culture

41:15 – How to handle low traffic scenarios in experiments

43:20 – Turning trending workforce issues into actionable metrics

45:45 – Balancing statistical rigor with real-world constraints in niche markets

47:30 – Final advice: Focus on problem-solving, not just tool mastery

48:40 – Closing thoughts: The future of prototyping and team roles

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By Software Oasis