Ep33: What AI Product Development Will Look Like in 5 Years

https://is1-ssl.mzstatic.com/image/thumb/Podcasts221/v4/5f/d3/23/5fd32383-da81-1720-d1ad-89ed035e5652/mza_9362998999783127206.jpg/600x600bb.jpg

Data Neighbor Podcast

40 episodes

1 day ago

Welcome to the Data Neighbor Podcast with Hai, Sravya, and Shane! We’re your friendly guides to the ever-evolving world of data. Whether you’re an aspiring data scientist, a data professional looking to grow your career, or just curious about how data shapes the world, you’re in the right place. Our mission? To help you break in or thrive in the field of data. We dive into: - Personal career journeys and how luck, opportunity, and grit play a role - How to break into the data field even with a non-traditional background - Industry insights through engaging conversations and expert interviews

Technology

RSS

All content for Data Neighbor Podcast is the property of Data Neighbor Podcast and is served directly from their servers with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.

Technology

https://d3t3ozftmdmh3i.cloudfront.net/staging/podcast_uploaded_nologo/42494603/42494603-1740459091702-43cb4d177b46d.jpg

Ep33: What AI Product Development Will Look Like in 5 Years

Data Neighbor Podcast

1 hour 7 minutes 56 seconds

4 months ago

Ep33: What AI Product Development Will Look Like in 5 Years

AI is fundamentally changing how we build and manage products—but agentic AI takes things to an entirely new level. In this episode of the Data Neighbor Podcast, we’re joined by Mahesh Yadav, who has built and launched AI-driven products at leading FAANG companies including Microsoft, Meta, Amazon, and Google. He’s also the creator of the popular Maven course on Agentic AI Product Management: https://maven.com/mahesh-yadav/genaipmMahesh shares firsthand insights into how the product lifecycle for AI-driven features differs from traditional development, the critical importance of robust evaluations, and how teams can practically adapt to the rapidly evolving landscape of AI. Whether you're a product manager, data scientist, engineer, or executive navigating the complexities of integrating AI into your products, this episode is your practical guide to thriving in the AI-first world.In this episode, you'll learn:- How the product lifecycle for agentic AI products differs from traditional software.- Practical frameworks for effectively evaluating AI performance and quality.- The role of subject matter experts and evaluation scientists in scaling AI products.- Strategies for staying ahead as AI reshapes traditional roles and team structures.Connect with Mahesh Yadav:🔗 LinkedIn: https://www.linkedin.com/in/initmahesh/🎓 Maven Course on Agentic AI Product Management: https://maven.com/mahesh-yadav/genaipmConnect with Shane, Sravya, and Hai (let us know which platform sent you!):👉 Shane Butler: https://linkedin.openinapp.co/b02fe👉 Sravya Madipalli: https://linkedin.openinapp.co/9be8c👉 Hai Guan: https://linkedin.openinapp.co/4qi1r

#ai #agenticai #productmanagement #productdevelopment #llms #aiproductmanagement #aiagents #aieval #evaluationmetrics #machinelearning #datascience #faang #productstrategy #dataanalytics #dataneighbor #businessintelligence #productleadership