How can product leaders build curious and collaborative teams? In this episode of Product Talk hosted by Jonathan Ozeran, Productiv Founder Jody Shapiro discusses his career in product management and insights on building successful teams. He speaks on his diverse educational background and how it led to roles at companies like TiVo and Google. Jody also shares strategies for constructing teams at startups, emphasizing passion and collaboration. Tune in for insights on how data-driven decision making and customer feedback can validate product ideas.
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Show Notes
- The importance of curiosity in driving innovation.
- Pursuing diverse educational backgrounds that complement each other.
- Gaining experience in both technical and business roles.
- Constructing teams deliberately with the right skills and mindsets.
- Prioritizing passion, creativity, and collaboration for early-stage startups.
- Avoiding assumptions and understanding local user needs in new markets.
- Learning from challenges of expanding products internationally.
- Validating product ideas through qualitative and quantitative research.
- Using data to inform decisions, bring teams together, and avoid biases.
- Finding a balance between flexibility and rigidity in product development.
- Managing large software ecosystems across many applications.
- Taking a data-driven approach to address ecosystem challenges.
- Developing common data models and integration across sources.
- Future impacts of generative AI on interfaces, content, and workflows.
- Moving to more assistive and conversational experiences.
- Summarizing and filtering AI-generated content and insights.
- Generative AI helping product managers gain insights.
- AI addressing painful or inefficient parts of jobs.
- Continued experimentation and play with emerging technologies.
- Focusing innovation on improving user and customer experiences.
About the speaker
About the host
Jonathan is a product and operations leader, company builder, investor and advisor. He has assembled, scaled and led product, design, software engineering, hardware engineering and machine learning teams across numerous financing stages (pre-seed through Series G).