Product for Product Management

Matt Green & Moshe Mikanovsky
  • 5.0 (6)
  • TECHNOLOGY
  • UPDATED WEEKLY

Product for Product is a show hosted by Matt Green and Moshe Mikanovsky aimed at helping listeners navigate the growing depth of product management tools while also providing our insights into the categories that make up the PM role. We will take listeners with us on a journey of discovery through areas of product analytics, road mapping, productivity and many others. If you want to keep up with the latest in product management come along for the ride! Connect with us on LinkedIn: https://linkedin.com/in/mattgreenproduct https://linkedin.com/in/mikanovsky Connect with us on Youtube: https://www.youtube.com/@productforproduct

  1. EP 148 - AI Tools: V0, Replit and more with Adir Traitel

    1D AGO

    EP 148 - AI Tools: V0, Replit and more with Adir Traitel

    We’re keeping the AI Tools series rolling with Adir Traitel, entrepreneur, product leader, and early adopter of just about every vibe coding tool out there. Adir joins Matt and Moshe to share hard‑won lessons from building real apps with v0, Bolt, Replit, Figma Make, and more, all while running his own startup and consulting on product builds across industries. From his early days in project management and mobile app startups, through work with companies like Moovit and across FinTech, AgTech, and credit scoring, Adir has consistently been the “try it first” person for new build tools. In this episode, he breaks down what these platforms actually do well, where they fall short, and how product managers can use them responsibly for experiments, prototypes, and beyond. Join Matt, Moshe, and Adir as they explore: Adir’s journey from PM and founder to heavy user of vibe coding tools in his current startup His 3-layer view of the ecosystem: AI dev assistants (Cursor, Antigravity, Claude Code), front-end mockup tools (v0, Figma Make), and full‑product builders (Lovable, Base44, Bolt, Replit) V0: where it shines for quickly building functional UIs (like his electricity consumption app) and where it starts to crack Lovable: great for sites and simple flows, but not ideal for complex SaaS or CRM‑like products Bolt: fun and fast for concepts, but why it never got him close to production Replit: stronger agents and capabilities, but weaker UI output and surprising backend defaults that can get very expensive very quickly Figma Make and Google Stitch: when design quality trumps everything else, especially for SaaS interfaces The real costs of vibe coding: AI token spend, hosting/pricing traps, and why production economics matter as much as build speed What his “dream product” would look like, including multi‑agent environments, better security/privacy, and built‑in QA and CI/CD How all this is reshaping the product management role, and why curiosity and tool fluency are becoming must‑have skills And much more!Want to connect with Adir or learn more? LinkedIn: https://www.linkedin.com/in/adirtraitel/ Website: https://adirtraitel.com/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/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    1 hr
  2. EP 147 - AI Tools: CLEAR with Marcos Polanco

    FEB 4

    EP 147 - AI Tools: CLEAR with Marcos Polanco

    We’re continuing our AI Tools series with Marcos Polanco, engineering leader, founder, and ecosystem builder from the Bay Area, who joins Matt and Moshe to introduce CLEAR, his method for using AI to build real software, not just demos.  Drawing on decades in software development and his recent research into how AI is reshaping the way teams ship products, Marcos shares how CLEAR gives both technical and non‑technical builders a production‑oriented way to work with vibe coding tools.Instead of treating AI like a magical black box, Marcos frames it as an “idiot savant”: incredibly capable and eager, but with no judgment. CLEAR wraps that raw power in structure, guardrails, and engineering discipline, so founders and PMs can go from prototype to production while keeping humans in control of the last, hardest 20%. Join Matt, Moshe, and Marcos as they explore: Marcos’s journey through engineering, founding, and AI research, and why he created CLEAR Why AI tools like Bolt, Cursor, Claude, and Gemini are fabulous for prototypes but risky for production without a method CLEAR in detail: C – Context: onboarding AI like a new hire, using stories and behavior‑driven design (BDD) to articulate requirements L – Layout: breaking work into focused, scoped pieces and choosing a tech stack so AI isn’t overwhelmed E – Execute: applying test‑driven development (TDD), writing tests first, then having AI write code to pass them A – Assess: using a second, independent LLM as a QA agent, plus a human‑run 5 Whys to fix root causes upstream R – Run: shipping to users, gathering new data, and feeding it back into the next iteration of context How CLEAR lowers cognitive load for both humans and AIs and reduces regressions and hallucinations Why Markdown (with diagrams like Mermaid) is becoming Marcos’s standard format for shared human–AI documentation How CLEAR changes the coordination layer of software development while keeping engineers central to quality and judgment Practical advice for PMs and founders who want to move from “just vibes” to predictable, production‑grade AI development And much more! Want to go deeper on CLEAR or connect with Marcos? CLEAR on GitHub: https://github.com/marcospolanco/ai-native-organizations/blob/main/CLEAR.md CLEAR slides: https://docs.google.com/presentation/d/1mwwDtr7cCP5jLUyNVgGR5Aj-MBq8xsMlhSc0pvSQDks/edit?usp=sharing LinkedIn: https://www.linkedin.com/in/marcospolanco 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 Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    52 min
  3. EP 146 - AI Tools: Base44 with Yaron Lavie

    JAN 21

    EP 146 - AI Tools: Base44 with Yaron Lavie

    We’re excited to continue our AI Tools series with Yaron Lavie, a veteran product leader with over 25 years of experience in FinTech, InsurTech, and now retail tech at Nexite, where he helps fashion retailers unlock unique in-store data.  In this episode, Yaron joins Matt and Moshe to share how he used Base44, an AI-powered, full‑stack vibe coding platform, to take a completely new product idea from concept to a deployed prototype without touching his R&D team. Yaron walks through why traditional approaches like Figma mockups and static visuals weren’t enough for the kind of validation he needed, and how he experimented with tools like Gemini, Claude, and ChatGPT before landing on Base44 for an end‑to‑end, fully hosted solution. He explains how Base44’s conversational, chat-based builder let him model user personas, flows, and entities, then iteratively refine an interactive analytics dashboard with real (anonymized) data, all inside a time‑boxed, low‑risk experiment that still respected security constraints. Join Matt, Moshe, and Yaron as they explore:Why Yaron needed to validate a new product idea without pulling scarce R&D resources off other priorities How he moved from static mockups to interactive prototypes with real data, and where Gemini helped and fell short What made Base44 stand out versus other vibe coding tools like Lovable: full-stack, hosted, and truly end-to-end The importance of “context engineering” over simple prompt engineering when building with LLM-based builders Using Base44’s discussion mode, live preview, and QA test generation to shape the product before committing to code Real-world limits: hitting a ceiling on UX depth, inflated code, and friction with design systems and engineering standards How he transitioned from a Base44 prototype to a ground-up rebuild with the core dev team, using the prototype to generate user stories Practical pros and cons: integrations, multi-currency support, database control, and when full-stack vibe coding is “good enough” Where Yaron sees vibe coding going next, and how PMs can use it responsibly for experimentation and usability testing And much more! Want to connect with Yaron or learn more?LinkedIn: https://il.linkedin.com/in/yaronlavie 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 Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    55 min
  4. EP 145 - AI Tools: N8N with Stav Charkham

    JAN 7

    EP 145 - AI Tools: N8N with Stav Charkham

    We’re excited to welcome Stav Charkham, Business Product Builder at Voyantis, former Product Manager and founder in EdTech, and seasoned automation expert, for a standout episode on using n8n and agentic AI to empower product managers and teams.Stav takes us through his journey from building products with no-code tools like Bubble and iPaaS tools like Make, to his current work scaling business workflows with AI, n8n, and internal systems at Voyantis. Learn how Stav helps teams go from research to business value in days, sometimes even hours, by combining open-source automation, hands-on user insight, and a bias for action.Join Matt, Moshe, and Stav as they explore: - What makes n8n different: open source, secure, and ready for power users, or anyone who wants to build without a developer - The basics of agentic AI: moving beyond IF/THEN logic, with “agents” that make real decisions using LLMs, memory, and a toolset - Practical use cases: how to save hours on manual work, analyze massive amounts of meeting data, and surface business opportunities using AI-powered automations - How Product Managers can independently build tools for their needs, deploying automations without writing code - n8n’s interface and workflow, and where technical skill might still required - Open source advantages and trade-offs: privacy, flexibility, cost, and the challenge of building and maintaining integrations - Why automation costs matter, and Stav’s real-world tips for measuring and optimizing LLM call expenses - Agentic vs. traditional workflows: when to use an AI agent, and when it’s not worth the extra cost or unpredictability - Cautionary tales and improvement wishes for n8n: integration gaps, edge cases, technical hurdles, and the ongoing quest for less technical UX - Kadabra, another tool Stav loves, combining automation frameworks with front-end flexibility - And much more! Want to connect with Stav or learn more? - LinkedIn: https://www.linkedin.com/in/st... You can also connect with us and find more episodes: - Product for Product Podcast: http://linkedin.com/company/pr... - Matt Green: https://www.linkedin.com/in/ma... - Moshe Mikanovsky: http://www.linkedin.com/in/mik... Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    56 min
  5. EP 144 - AI Tools: Lovable with Elena Levi

    12/24/2025

    EP 144 - AI Tools: Lovable with Elena Levi

    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: 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! Want to connect with Elena or learn more? LinkedIn: https://www.linkedin.com/in/elena-levi-data 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 Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    52 min
  6. EP 143 - AI Tools: Using AI Securely with Eva Gao

    12/10/2025

    EP 143 - AI Tools: Using AI Securely with Eva Gao

    We’re thrilled to welcome back Eva Hongyan Gao, Head of Product ESG at AMCS Group, a returning guest (episode 102) and a product leader in B2B SaaS, circular economy, and ESG, for a special episode on using LLMs securely inside the enterprise. Eva joins Matt and Moshe to offer a candid, hands-on look at how AI fits into enterprise toolkits, the challenges of data compliance, and the realities of integrating tools like Microsoft Copilot Studio within strict security frameworks. Eva brings deep experience building for demanding enterprise customers, where success is measured not just by innovation, but by strict ISO, SOC 2, and GDPR compliance. She shares what happens behind the scenes as product leaders and IT teams try to balance innovation, cost, and data protection, sometimes losing sleep over responsible tool usage and ever-climbing AI integration costs. Join Matt, Moshe, and Eva as they explore:Using AI tools in highly regulated, security-conscious B2B enterprise settings The compliance process: from ISO and SOC2 to GDPR and internal AI guidelines Why Microsoft Copilot is becoming the default LLM in enterprises, and what you still need to watch out for Building internal agents and chat interfaces to answer roadmap questions and handle stakeholder requests Lessons learned moving from over-engineered platforms to simpler, compliant AI tools Creative AI workflows, including removing branded assets between Copilot and Figma and orchestrating information for various departments The ongoing struggle: data redaction, internal transparency, and the limits of controlling generative models LLM orchestration: mixing old-school logic with new AI capabilities, and knowing when not to use AI Security best practices and the importance of a trust-based compliance mindset across the organization What happens when stakeholders use AI tools in ways product never expected Opportunities for Copilot and DevOps to streamline maintenance, documentation, and stakeholder requests The future of AI in sustainability, product management, and business decision-making And much more! Want to connect with Eva or learn more?LinkedIn https://www.linkedin.com/in/evagaode You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproductMoshe Mikanovsky: http://www.linkedin.com/in/mikanovsky Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    53 min
  7. EP 142 - AI Tools: LLMs with Sani Manic

    11/26/2025

    EP 142 - AI Tools: LLMs with Sani Manic

    We continue our AI Tools series with a deep dive into using Large Language Models (LLMs) for research, featuring Slobodan (Sani) Manić, AI skeptic, podcaster, and founder of the AI Fluency Club. Sani joins Matt and Moshe to share why context, careful prompting, and critical thinking are essential for getting real value out of today’s LLMs in product work. Drawing on his work as a product builder, educator, and host of No Hacks Podcast, Sani challenges common myths about AI’s capabilities and underscores both its practical uses and its risks for product managers. The conversation ranges from practical workflows to future visions of invisible AI, open-source models, and the real state of the “wrapper economy” built on major LLM providers. Join Matt, Moshe, and Sani as they explore: - Why most LLM workflows boil down to two mindsets: understanding your work, or avoiding understanding it - The crucial role of context and authority, why careless prompting leads to hallucinations, and how to break questions into smaller steps for better results - How LLMs fit as accelerators for deep research, surfacing insights faster than classic search engines, but always requiring fact-checking - Why Sani uses Google’s Gemini and NotebookLM, and the value of integration with your company’s existing tools - The open-source LLM alternative: privacy, flexibility, and why some see this as the future for secure enterprise AI - Pitfalls of the “wrapper economy,” vendor lock-in, and shaky business models based on reselling tokens - Starting out: how to include LLMs in PM research without reinventing your workflow, and why you must be careful with company data - The risks and limitations of AI today, especially in enterprise and sensitive environments - How internal AI context in tools like Atlassian makes those LLM features uniquely powerful - Future predictions: AI that fades into the background, plus the big unanswered questions about interface and humanoid robots - Sani’s approach to AI education, success stories from AI Fluency Club, and what executives need to learn to stay ahead - And much more! Want to learn more or join Sani’s community? - LinkedIn: Slobodan (Sani) Manić https://www.linkedin.com/in/sl... - No Hacks Podcast http://nohackspod.com/ - AI Fluency Club https://aifluencyclub.com/ You can also connect with us and find more episodes: - Product for Product Podcast http://linkedin.com/company/pr... - Matt Green https://www.linkedin.com/in/ma... - Moshe Mikanovsky http://www.linkedin.com/in/mik... Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    46 min
  8. EP 141 - AI Tools: Kickoff with Matt and Moshe

    11/12/2025

    EP 141 - AI Tools: Kickoff with Matt and Moshe

    We’re excited to launch a brand-new series on the Product for Product Podcast, with Matt and Moshe diving deep into the world of AI tools for product managers. In this special episode, we set the stage for upcoming conversations by exploring how AI is becoming an indispensable partner in every stage of the product management journey. Join us as Matt and Moshe discuss: - The rapidly evolving role of AI throughout the product management workflow, from idea generation and discovery to strategy, prioritization, delivery, launch, and ongoing monitoring - The importance of using AI as a tool for knowledge and insight, rather than replacing critical thinking and understanding - How product managers can leverage Large Language Models (LLMs) for research, writing, and scenario planning - The realities and limitations of today’s AI tools, including the challenges of ensuring accuracy and context in product work - Exploring the promise of AI platforms for rapid prototyping and MVP testing - How AI can help bridge the gap between prototyping and actually building production-ready products - Using AI to inform strategic decisions, pricing, packaging, prioritization, and risk assessment - Integrating AI into your board and backlog systems for smarter feedback synthesis and decision-making - Enhancing sprint-based development with AI-generated user stories, acceptance criteria, and more - Upcoming content around data consolidation, go-to-market strategies, and ways AI is changing the PM discipline - And much more! Whether you’re just starting to experiment with AI or looking to deepen how you use it in your product practice, this series is for you. Stay tuned for practical examples, case studies, and discussions that will help you harness the latest AI tools, while remembering that the best PMs know how to balance tech innovation with human judgment.Connect with us and follow the rest of the series: - Product for Product Podcast http://linkedin.com/company/pr... - Matt Greenhttps://www.linkedin.com/in/ma... https://www.linkedin.com/in/ma... - Moshe Mikanovsky http://www.linkedin.com/in/mik... Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

    33 min
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About

Product for Product is a show hosted by Matt Green and Moshe Mikanovsky aimed at helping listeners navigate the growing depth of product management tools while also providing our insights into the categories that make up the PM role. We will take listeners with us on a journey of discovery through areas of product analytics, road mapping, productivity and many others. If you want to keep up with the latest in product management come along for the ride! Connect with us on LinkedIn: https://linkedin.com/in/mattgreenproduct https://linkedin.com/in/mikanovsky Connect with us on Youtube: https://www.youtube.com/@productforproduct

Information

  • Creator
    Matt Green & Moshe Mikanovsky
  • Years Active
    2021 - 2026
  • Episodes
    149
  • Rating
    Explicit
  • Copyright
    © Copyright Matt Green & Moshe Mikanovsky
  • Show Website
    Product for Product Management

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