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.

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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 ⭐️⭐️⭐️⭐️⭐️

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 ⭐️⭐️⭐️⭐️⭐️

As we continue our tradition of highlighting innovative startups building for product professionals, we’re excited to introduce Matan Kleyman, CEO and Co-Founder of Hunch, on this week’s episode.

On the show, Matan shares his journey from technical engineering and data science roles to leading product teams and hosting a podcast focused on AI and product management. Now with Hunch, he’s set out to solve a problem many product managers know well: after all the investment in collecting and aggregating data, only a handful of senior data engineers truly know how to use it.

With that problem in mind, Hunch is on a mission to democratize data access, giving product people rapid, autonomous, and approachable ways to get insights, act on their hunches, and unlock value from their company’s data.

Join Matt and Moshe as they explore with Matan:

• The founding story of Hunch and why product managers are at the center of their vision
• How Hunch enables any team member to query data using a ChatGPT-like interface and ready-made templates
• Turning raw insights into dashboards and customizable data apps with no technical background required
• Hunch’s two big differentiators: optimizing for speed and for true autonomy
• Real-world use cases, from engineers and PMs, to data-driven decision-making in action
• How Hunch supports both quantitative (what happened in the product) and qualitative (what should happen next) analysis, including transcript integrations
• Matan’s philosophy on building trust: prioritizing transparency over rigid accuracy and giving users control over context
• Best practices for onboarding, context management, and building knowledge sets in Hunch
• Lessons from building their public roadmap and belief in open, user-driven product development
• The future of product management as a hybrid of visionary leadership and orchestration
• And much more!

Curious to try Hunch or learn more? Connect with Matan:

• LinkedIn: https://www.linkedin.com/in/matankleyman/ 
• Hunch: https://www.hunch.dev/
  

You can find the podcast’s page, and connect with Matt and Moshe on LinkedIn:

• Product for Product Podcast
• Matt Green
• Moshe 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 ⭐️⭐️⭐️⭐️⭐️

As we traditionally have done in previous years, we’re excited to feature innovative founders who are building exciting tools for product professionals. Continuing our Startups of 2025 series, we welcome Nathan Ngai, CEO and founder of Arkhet.

On the show, we explore with Nathan his journey—from over a decade in product design, running countless discovery workshops and design sprints, to becoming a founder aiming to rethink how AI can work for product people. Frustrated by the boom of AI tools that overpromised yet underdelivered, Nathan set out to build Arkhet—an AI-powered wireframing and prototyping platform designed to give product managers and teams more control, speed, and clarity.

With Arkhet, instead of relying solely on the back-and-forth of prompt engineering (and getting results you didn’t ask for), users start visually—building wireframes and layering prompts on top of them. It’s a purposeful approach: if you know what you want to build, Arkhet lets you highlight and describe specific sections, apply your style guide, and collaborate more effectively with designers. The short-term goal: empower PMs to create prototypes faster and more collaboratively, with future possibilities that could extend into full product builds.

Join Matt and Moshe as they explore with Nathan:

• The founding story of Arkhet and why visual prompting solves a major gap in today’s AI tools
• How Arkhet integrates the best of traditional wireframing with generative AI to speed up prototyping
• The differences between Arkhet and other AI design/prototyping products
• How it streamlines the collaboration between product managers and designers
• Beta success stories and why Product Managers are choosing Arkhet over other AI tools
• Pivoting from a designer-first ICP to focusing on Product Managers—and why both roles will remain crucial
• Why AI won’t replace Product Managers or designers, but can help them work better and faster
• The roadmap for style guide personalization, Figma integration, and beyond
• And much more!

You can connect with Nathan at:

• LinkedIn: https://www.linkedin.com/in/ngainathan/
• Arkhet

You can find the podcast’s page, and connect with Matt and Moshe on Linkedin: 

• Product for Product Podcast - linkedin.com/company/product-for-product-podcast
• Matt Green - linkedin.com/in/mattgreenproduct/
• Moshe Mikanovsky - 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 ⭐️⭐️⭐️⭐️⭐️