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July 6, 2024 44 mins
Summary Summary In this conversation, Cyrus and Lauren discuss the intersection of Agile and data science, specifically focusing on the challenges of shipping AI-enabled products quickly. They emphasize the importance of democratizing AI within organizations and the need for product managers to understand AI and ML concepts. They also discuss the prioritization of AI ML feature sets per quarter and the balance between quick wins and long-term strategic initiatives. Lauren shares her recommendations for getting buy-in and support from leadership, including listening, scenario planning, and making informed decisions. Takeaways Democratizing AI within organizations is crucial for enabling more people to understand and work with AI and ML. Product managers should prioritize AI ML feature sets based on business goals and market expectations. Balancing quick wins and long-term strategic initiatives is important for delivering outcomes and driving growth. Getting buy-in and support from leadership requires listening, scenario planning, and making informed decisions. Understanding the constraints and goals of different teams and stakeholders is essential for successful product management in the AI ML space. Chapters 00:00 Introduction and Background 03:25 Challenges of Delivering Business Value Quickly 06:52 Democratizing AI within Organizations 11:05 Scoping AI/ML Feature Sets for Revenue Outcomes 14:12 Staying Up-to-Date with New Technologies 27:40 Incorporating AI into Product Strategies 28:54 Aligning Organizational Expectations and Goals 30:09 Understanding Constraints and Goals 33:10 Planning and Execution 36:04 Balancing Quick Wins and Long-Term Strategic Initiatives 40:17 Gaining Buy-In from Leadership 43:10 Democratizing Knowledge about AI and ML Keywords Agile, data science, intersection, challenges, shipping, AI-enabled products, democratizing AI, product managers, prioritization, feature sets, quick wins, long-term strategic initiatives, buy-in, leadership
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