EP 144 - AI Tools: Lovable with Elena Levi
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A proposito di questo titolo
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!
- LinkedIn: https://www.linkedin.com/in/elena-levi-data
- 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
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