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 151 - Gender Based Data Analytics with Lea Khasidi

    3D AGO

    EP 151 - Gender Based Data Analytics with Lea Khasidi

    We’re excited to welcome Lea Khasidi, product management freelancer, founder and CEO of MaPott, and soon‑to‑be author, for a powerful conversation on gender-based data analytics for product managers. Lea shares her journey from intelligence work in the IDF, through product roles in EdTech, cybersecurity, and beyond, to founding a health management app for women with chronic conditions. Along the way, one pivotal discovery while consolidating four cybersecurity platforms, seeing men and women use the same filtering feature in completely different ways, sparked her deep focus on how gender shapes behavior in our products, especially in B2B contexts where it’s often ignored. Join Matt and Moshe as they explore with Lea:How a real-world analytics puzzle revealed stark gender differences in workflow, and changed how she thinks about usage data The three pillars of context we can’t change (who users are, how they act, where they work) and the one we can: what we give them in the product How “hacks” and workarounds used by different genders can hint at your next features A practical system for existing products: using analytics to segment by gender, spotting behavioral differences, then following up with observation and interviews How to approach gender representation when validating new products, and why balanced samples matter even for seemingly “neutral” tools Ways to lean on existing research about gender patterns in your domain (health, education, finance, etc.) instead of guessing from scratch Why early-stage startups should ship faster and learn from usage, while mature products might rely more on A/B tests and targeted outreach The risk of building solely from our own biases and assumptions, and why gender should be on the PM checklist, even if it’s not always the first lens Lea’s upcoming book on gender-based analytics for PMs One piece of advice she has for founders learning to trust their insight while staying open to the data And much more! Want to connect with Lea or learn more?LinkedIn: https://www.linkedin.com/in/lea-khasidi/ Website: https://leakhasidi.comMaPott: https://www.ma-pott.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/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 ⭐️⭐️⭐️⭐️⭐️

    49 min
  2. EP 150 - OHLA Framework with Radhika Dutt

    MAR 18

    EP 150 - OHLA Framework with Radhika Dutt

    We’re delighted to welcome Radhika Dutt, product leader, founder, and author of Radical Product Thinking, for a deep dive into her newest work: the OHLA (formerly OHL) Toolkit.  In this episode, Radhika joins Matt and Moshe to challenge how product teams set goals, measure progress, and use frameworks, proposing a puzzle‑driven alternative to traditional OKRs and “framework-following” culture. Drawing from her journey from electrical engineering and startups at MIT, through painful “product diseases” like Hero Syndrome and Obsessive Sales Disorder, Radhika shares why recipes and templates alone don’t create real progress. Instead, she introduces OHLA as a lightweight but powerful way to cultivate a Jedi mindset, one that keeps teams grounded in first principles, context, and learning rather than chasing vanity metrics and rigid targets. Join Matt, Moshe, and Radhika as they explore:Radhika’s path from engineering and founding to Radical Product Thinking and now the OHLA Toolkit Why classic goal‑setting and OKRs often backfire, creating “alibi progress,” outdated goals, and incentives to hide bad news OHLA in practice: Observe – what’s really happening in your product, team, or market Hypothesize – what might explain it and how you’ll test those ideas Learn – what the results actually tell you Adapt – how you’ll change course based on evidence “Puzzle setting” vs goal setting: defining puzzles with Observation, Open Questions, and an Objective summary to stay longer in the problem space How OHLA complements design thinking by forcing teams to remain curious and uncomfortable before jumping into solutions Practical stories, from maritime platforms to enterprise teams, where puzzle thinking led to very different solutions than OKR‑driven targets How managers can shift conversations from “Did we hit the number?” to “How well did it work? What did we learn? What will we try next?” A realistic path to transition: starting with your own puzzle, then introducing OHLA within your immediate sphere of influence And much more! Want to explore the OHLA Toolkit or connect with Radhika?OHLA Toolkit: https://www.radicalproduct.com/toolkit/#OHLToolkit Radical Product site: https://www.radicalproduct.com/ LinkedIn: https://www.linkedin.com/in/radhikadutt/ 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 ⭐️⭐️⭐️⭐️⭐️

    54 min
  3. EP 149 - AI Tools: Summary with Matt & Moshe

    MAR 4

    EP 149 - AI Tools: Summary with Matt & Moshe

    We’re wrapping up our AI Tools series with a special episode featuring just the two of us—Matt and Moshe—looking back at what we really learned (and where we’re still confused) about AI in product management. Across this conversation, we revisit the core themes that emerged with our guests and in our own experiments: from “vibe coding” and no‑code builders, to LLM assistants, enterprise privacy, agentic workflows, and the evolving role of the product manager.  We share candid stories of using tools like Google Stitch, Figma/Figma Make, FlutterFlow, Base44, and others to design and prototype a real mobile app; what worked, what broke, and why credits, pricing, and model limits matter far more than the glossy demos suggest. Join Matt and Moshe as they explore: How our AI Tools series evolved, from “let’s review tools” to “AI is not one thing, it’s many different problem spaces”Why “vibe coding” is a misleading umbrella term, and how it means something different to devs, PMs, and designersLessons from using AI for design and prototyping: inconsistent outputs, beta‑stage rough edges, and the pain of credit-based modelsBuild vs. buy for AI: integrating foundation models vs. building your own, and what that means for pricing, UX, and reliabilityEnterprise realities: privacy, security, and why tools like Copilot/Gemini have such an advantage where data and IT policies matterHow conversations with our guests (Sani, Eva, Elena, Stav, Yaron, Marcos and Adir) shifted our thinking about workflows, orchestration, and agentsThe future of agent-to-agent interactions: what happens when AIs negotiate purchases and workflows with minimal human promptsWhy first principles and business outcomes still matter more than any single AI toolHow the PM role is changing: less tool‑chasing, more orchestration, strategy, and clarity about what problem we’re actually solvingWhat topics we’d tackle next, like pricing, packaging, and credit models for AI products, and how this series is shaping our own careersAnd much more!You can connect with us and keep following what comes after this AI Tools series: Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt 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 ⭐️⭐️⭐️⭐️⭐️

    41 min
  4. EP 148 - AI Tools: V0, Replit and more with Adir Traitel

    FEB 18

    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
  5. 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
  6. 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
  7. 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
  8. 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
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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
    152
  • Rating
    Explicit
  • Copyright
    © Copyright Matt Green & Moshe Mikanovsky
  • Show Website
    Product for Product Management

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