#110 Saranyaa Parthikumar: Building Products in the AI Era, With Trust, Speed, and Human Judgment

Saranyaa Parthikumar shares her journey from Java developer to MBA, then Lead Business Analyst, and finally Product Manager. She explains how the switch happened through an internal move: raising her hand, talking to managers, taking on junior PM style projects, and building confidence by representing the customer and guiding delivery.Saranyaa describes the kind of products where she shines: B2C experiences and data heavy platforms where research, segmentation, and experimentation matter. She shares the biggest shift after becoming a PM: your calendar becomes everyone’s calendar. The role demands constant context switching and influence across design, engineering, research, marketing, and go to market partners, while keeping communication clear so the whole team moves in one direction.They explore why Saranyaa loves zero to one work most. She compares it to detective work: starting with an ambiguous problem, collecting evidence, prototyping, shaping a narrative, and then rallying the team to execute. She defines good product management as starting in the user’s shoes, understanding the real pain, and translating that into something technology can deliver.On AI, Saranyaa says it became central in the last eight months through GenAI tools that let her create working prototypes early. This makes it easier for teams to visualize ideas, ask sharper questions, and move faster with clearer documentation. She believes teams will become more fluid as AI lowers the barrier between roles, with people flexing into analytics, product, or execution based on the sprint.Saranyaa also pushes back on the fear that AI will replace humans. AI is strong at automation and summarizing existing knowledge, but humans remain essential for judgment, creativity, direction, and guardrails. For AI products, she emphasizes rigorous testing, human in the loop reviews, and safety and sensitivity guardrails. When launching AI features, her most important metric is trust, because once users feel uncertain about how data and memory are handled, adoption suffers.She closes with advice for aspiring PMs: do not hesitate. Strong communication, collaboration, and empathy still matter most. Use GenAI tools to build small side projects, learn by shipping, gather feedback, iterate, and use those wins to earn the role. Her final reminder is simple: you do not need an engineering degree to become a PM, you need customer understanding and the willingness to learn.About Saranyaa Parthikumar:- https://www.linkedin.com/in/saranyaap/About Federico Ramallo ✨👨‍💻🌎🚀 Software Engineering Manager | 🛠 Founder of DensityLabs.io & PreVetted.ai | 🤝 Connecting 🇺🇸 U.S. teams with top nearshore 🌎 LATAM engineers- 💼 https://www.linkedin.com/in/framallo/- 🌐 https://densitylabs.io- ✅ https://prevetted.ai🎙 PreVetted Podcast 🎧📡- 🎯 https://prevetted.ai/podcast- 🐦 https://x.com/PrevettedPod- 🔗 https://www.linkedin.com/company/prevetted-podcast00:00 Introduction to Product Management and AI01:39 Transitioning from Business Analyst to Product Manager04:29 The Role of a Product Manager08:11 Navigating the Zero to One Phase10:29 The Impact of AI on Product Management15:57 AI's Role in Job Evolution19:26 Skills for Future Product Managers23:03 Ensuring Trust in AI Products26:09 Advice for Aspiring Product Managers