What does it take to go from a great product manager to a true Super PM in the AI era? In this roundtable hosted by Products That Count CEO Hoda Mehr, members of the Products That Count AI Advisory Council—Samsara Inc Senior Business Operations Manager Suryakant Kasushik, Vail Systems Product Manager Swetha Viswanatha, Clio AI Product Lead Keyuri Anand, and Walmart Principal Product Manager Ankit Raheja—explore the skills, competencies, and strategic thinking required to build and lead AI-powered products. They break down the three-layer AI competency framework, examine how evals are reshaping product development, and share insights on how PMs can assess and accelerate their own AI mastery.
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Show Notes:
- AI mastery is built on three layers of competency: using AI, building with AI, and leading with AI.
- Using AI has become a foundational skill for PMs, centered on prompt mastery and productivity.
- Prompt writing now functions as a core competency that shapes how effectively PMs can leverage models.
- Building with AI adds new responsibilities, including understanding data, models, and system architecture.
- Evals are becoming central to product development, acting as the quality benchmark for accuracy and safety.
- AI products are nondeterministic, making testing more complex and requiring deeper PM involvement.
- Governance, compliance, and responsible AI practices are essential parts of modern product development.
- AI-driven outcomes change the economics of product pricing, especially because inference costs scale.
- PMs must learn when to use rule-based approaches versus AI-powered ones.
- Data strategy is becoming a competitive moat, influencing differentiation and defensibility.
- AI unlocks new value by enabling software to perform tasks previously done manually.
- Cross-functional collaboration expands, requiring PMs to work closely with ML, design, legal, and data teams.
- Leading with AI requires shaping long-term product strategy and anticipating shifts in models and markets.
- Design choices influence differentiation, especially as conversational interfaces become standard.
- Storytelling becomes even more important for communicating AI value to executives and teams.
- Eval frameworks can serve as a company’s moat because accuracy drives adoption.
- PMs need to understand the cost structure of AI, particularly the impact of recurring model calls.
- The PM role now intersects more deeply with data science, including metrics, evaluation, and data quality.
- Self-assessment helps PMs identify their strengths, gaps, and growth paths within the AI competency layers.
- The AI competency framework can also help PMs evaluate companies’ AI maturity when considering roles.
About the speaker
Products that Count is a 501(c)3 nonprofit that helps everyone build great products. It celebrates product excellence through coveted Awards that inspire 500,000+ product managers and honor great products and the professionals responsible for their success. It accelerates the career and rise to the C-suite of >30% of all Product Managers globally by providing exceptional programming – including award-winning podcasts and popular newsletters – for free. It acts as a trusted advisor to all CPOs at Fortune 1000, and publishes key insights from innovative companies, like Capgemini, SoFi, and Amplitude, that turn product success into business success.