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EP 144 - AI Tools: Lovable with Elena Levi
About this Episode
We’re excited to bring on Elena Levi, Director of Product Management at Payoneer, data analytics veteran, and passionate advocate for product-driven teams, for a special episode exploring what it’s really like to use Lovable and other AI-powered vibe coding tools in product development.
Elena shares insights from 15 years in data analytics and product, with the journey from data analyst to product leadership fueling her curiosity about how AI can reshape prototyping, design, and collaboration. Drawing from hands-on experience building predictive analytics solutions, Elena reveals why she chose Lovable for fast prototyping, user testing, product sense interviews, and collaborating with both developers and designers.
Join Matt, Moshe, and Elena as they explore:
You can also connect with us and find more episodes:
Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️
Elena shares insights from 15 years in data analytics and product, with the journey from data analyst to product leadership fueling her curiosity about how AI can reshape prototyping, design, and collaboration. Drawing from hands-on experience building predictive analytics solutions, Elena reveals why she chose Lovable for fast prototyping, user testing, product sense interviews, and collaborating with both developers and designers.
Join Matt, Moshe, and Elena as they explore:
- The strengths and limitations of Lovable for prototyping: rapid iteration, easy sharing, changing flows on the fly, user testing, and developer handoff
- When vibe coding works, and where you still need engineering and design expertise
- The realities of code generation, versioning, Supabase integration, and why Lovable stood out from the competition at the time she chose it
- Using Lovable for product sense interviews
- Practical tips: breaking tasks into smaller prompts, saving tokens with up-front documents, and why the first prompt is the most important
- The trade-offs of using AI tools for MVPs, B2B vs. B2C products, and where privacy and maintainability concerns come in
- Responses from engineers and designers, what these tools mean for their work, learning curves, and whether they help or hinder junior team members
- Expectations vs. reality: how close AI tools get you to the finish line, and why “the last mile” is the toughest
- Conundrums, gotchas, frustrations, and how to keep flexibility in your workflow
- Why do PMs must always ask “Why?”, and why AI alone can't replace a critical data mindset
- And much more!
You can also connect with us and find more episodes:
- Product for Product Podcast: http://linkedin.com/company/product-for-product-podcast
- Matt Green: https://www.linkedin.com/in/mattgreenproduct
- Moshe Mikanovsky: http://www.linkedin.com/in/mikanovsky
Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️
Hosts & Guests
No transcript available for this episode.
