Product in Practice cover art

Product in Practice

Product in Practice

Written by: Atlassian
Listen for free

About this listen

 Product leaders show you exactly how they work - the frameworks, tools, and workflows they use to build great products. Every episode includes live demos and practical techniques you can use immediately, covering everything from prototyping and research to strategy and team collaboration. Walk away with tactics that make you better at the craft, not theory you'll forget tomorrow. Hosted by Axel Sooriah.Atlassian Economics
Episodes
  • Aakash Gupta: The skill every product manager must learn in 2026

    Aakash Gupta: The skill every product manager must learn in 2026
    Dec 18 2025

    What if you could build product prototypes in 15 minutes instead of 3 weeks?In this episode, Aakash Gupta (creator of the Product Growth Newsletter and former VP of Product at Affirm, Epic Games, and ThredUp) reveals the AI prototyping workflow that's revolutionizing product management.Watch as he live-demos building a sleep tracker app using Bolt, V0, and Lovable, showing you exactly how to go from concept to a working prototype in minutes.What You'll Learn:

    • The 6-step framework every PM needs to master AI product building
    • How to use Bolt, V0, Lovable & Cursor for rapid prototyping
    • Why AI prototyping is the most significant change product management has ever seen
    • Real-time demo: Building a sleep score calculator from scratch
    • The exact prompt engineering techniques that get better results
    • How to iterate across multiple AI tools to find the best output
    • Start with problem discovery (not jumping straight to solutions)
    • Test across multiple tools (Bolt, V0, Lovable)
    • Iterate with detailed feedback
    • Move to Cursor for final refinements

    The Four-Step AI Prototyping Method:"What used to take weeks now takes literally minutes." This isn't hype; this is the new reality for product builders.About Aakash Gupta: Long-time product leader at ThredUp, Epic Games, Affirm, and Apollo. He now runs the Product Growth Newsletter (Substack), featuring practical playbooks and AI experiments for product builders.Where to find Aakash Gupta:

    LinkedIn: https://www.linkedin.com/in/aagupta/


    Where to find Axel:

    Linktree: https://linktr.ee/axelsooriah

    LinkedIn: https://www.linkedin.com/in/axelsooriah/


    About Atlassian:

    Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.

    Connect with Atlassian:

    Subscribe: https://www.youtube.com/channel/UCL1yMVRMh3vxitPiVaXfkoA

    Follow Atlassian on LinkedIn: https://www.linkedin.com/company/atlassian

    Follow Atlassian on Instagram: https://www.instagram.com/atlassian/

    Follow Atlassian on X: https://x.com/atlassian

    Follow Atlassian on Facebook: https://www.facebook.com/Atlassian/

    If you're a PM, designer, or engineer building AI products, this is required viewing for 2025.
    Show More Show Less
    42 mins
  • Kene Anoliefo: How to build context libraries and raise AI fluency

    Kene Anoliefo: How to build context libraries and raise AI fluency
    Oct 22 2025

    Kene Anoliefo has led product and design at Google, Spotify, and Netflix. She founded Heard, an AI-powered user research platform, and is now building tools that help teams capture and structure institutional knowledge so both people and AI can produce high-quality work.

    We discuss

    • The three Ps of AI adoption: people, process, and platformWhy most companies jump to platform tools whilst ignoring the people problem
    • Moving from gatekeepers to architects in product organisations
    • Context enablement: turning implicit knowledge into explicit AI inputs
    • The coordination tax and how AI changes team collaboration
    • Why AI is like a brilliant but clueless new team memberBuilding context libraries to 10x your AI output quality


    Key takeaways

    Start with people, not platform tools. Most companies rush to buy AI tools whilst ignoring the deeper questions: Who am I in this AI era? What makes me valuable when AI can do parts of my job? Anxiety about AI is rooted in identity, not technology. Address the people layer first before investing in new platforms.

    Transform from gatekeepers to architects. Don't own user research, product strategy, or design - architect the principles and standards so anyone can do great work in those domains. With AI giving everyone superpowers, your value shifts from creating scarcity to enabling abundance.

    Context is your competitive advantage, not just data. AI trained on generic internet data produces generic output. Context libraries - structured repositories of your product strategy, design principles, customer segments, and research standards - help AI understand how your company builds products.

    AI is brilliant but clueless without your context. Think of AI as a talented new hire who needs onboarding. It has capabilities but no understanding of your product, customers, or how your team works. Just like you'd explain these things to a new employee, you need to provide this context to AI tools through documentation optimised for machine reading.

    Don't wait for permission to engage with AI. The biggest barrier isn't technical knowledge - it's mindset. You don't need to have worked at ML-first companies or taken AI courses. The cure for AI anxiety isn't trying to learn everything; it's starting with work you already love and asking how AI can make it 10-20% better.

    Chapters00:00: Introduction to Kene Anoliefo01:00: Kene's journey from Spotify and Netflix to founding Heard04:00: Early interest in AI and building AI-powered research tools07:00: Overcoming AI anxiety and intimidation10:00: The three Ps framework: people, process, and platform14:00: Why feelings matter more than tools in AI adoption15:00: The coordination tax and new team dynamics18:00: Gatekeeping vs enabling in the AI era20:00: Context enablement and knowledge architecture23:00: AI as a brilliant but clueless team member26:00: Career advice: take more shots on goal28:00: Making context enablement practical and actionable30:00: Demo: Building context libraries for AI33:00: Creating user research context libraries36:00: Using AI to generate context documentation39:00: Before and after: brainstorming without context42:00: The multiplier effect of context investment45:00: Context engineering as the next frontier48:00: Design context libraries and component repos51:00: Prototyping with V0 using pre-built contexts56:00: Democratising product ideas across the organisation59:00: Lightning round: staying sharp in the AI era01:01:00: Desert island books and dishes01:04:00: Final advice and where to find Kene

    Where to find Kene Anoliefo:LinkedIn: https://www.linkedin.com/in/kene-anoliefo-68a8b714/Website: https://kene.ai

    Where to find Axel:Linktree: https://linktr.ee/axelsooriahLinkedIn: https://www.linkedin.com/in/axelsooriah/

    #productmanagement #PM #atlassian

    About Atlassian:Behind every great human achievement, there is a team. We help teams advance humanity through the power of software.
    Show More Show Less
    1 hr and 6 mins
  • Ravi Mehta: Data-Driven Prototyping with AI

    Ravi Mehta: Data-Driven Prototyping with AI
    Oct 22 2025
    Ravi Mehta is a senior product executive with experience leading product organisations at TripAdvisor, Facebook, and Tinder. He's the co-creator of Reforge's AI Strategy Program and currently works as a product strategy adviser and investor.We discuss:Why some companies are vulnerable to AI disruption whilst others have years to adaptThe three cohorts in every organisation: evangelists, interested learners, and scepticsHow AI changes team collaborationWhy AI generates the averageThe shift from craft to tasteData-driven prototypingWhich PM skills are changing and which remain essentialKey takeawaysAI generates the average - both its strength and limitation. Large language models produce "good enough" results quickly, but strong products are outliers. Use AI's speed to iterate towards something better.Product work is splitting into human-speed and AI-speed activities. Understanding customers, strategy, and adoption happens at human speed. Documentation, prototypes, and design happens at AI speed. Focus on customer discovery, product sense, and strategy.The emphasis is shifting from craft to taste. AI is making craft accessible. When anyone can generate designs or prototypes, taste becomes the main differentiator. Determining what to build becomes 90% of success, up from 50%.Data-driven prototyping unlocks more testing. Start with the data schema, generate mock data, then ask AI to create an interface.Three cohorts exist: evangelists, interested learners, and sceptics. Evangelists experiment daily. Interested learners need access and education. Sceptics need to understand that AI is transforming work.Where to find Ravi Mehta:Website: https://www.ravi-mehta.com/Substack: Ravi on ProductLinkedIn: https://www.linkedin.com/in/ravimehta/Where to find Axel SooriahNewsletter: https://linktr.ee/axelsooriahLinkedIn: https://www.linkedin.com/in/axelsooriah/What we cover(00:00) Introduction to Ravi Mehta(01:00) Why Reforge created the AI Strategy Program(03:00) The four parts of AI strategy: disruption risk, market, product, and execution(04:00) Insights from running Reforge's inaugural AI Strategy program(06:00) Three ways to raise AI fluency across product teams(09:00) The most powerful move PMs are making with AI(11:00) Why AI is also "average intelligence" and what that means(13:00) Skills moving at human speed vs AI speed(15:00) The shift from craft to taste in creative work(18:00) Which PM competencies are changing and which remain essential(21:00) Can AI actually think? The nuanced answer(23:00) How AI is transforming product discovery(26:00) Demo: Introduction to data-driven prototyping(28:00) Spec-driven vs design-driven prototyping(30:00) Building a trip planning feature the traditional way(35:00) Generating structured data with Claude and MCP servers(39:00) Creating prototypes from data schemas(42:00) Iterating on features with separated data layers(45:00) Switching data sets to test different scenarios(49:00) Recommended resources for product managers(50:00) Developing product judgement through mindful observationReferencedReforge: https://www.reforge.comMagic Patterns: https://www.magicpatterns.comClaude MCP: https://modelcontextprotocol.ioSmithery: https://smithery.aiv0: https://v0.appLovable: https://lovable.devBolt: https://bolt.newGitLab: https://gitlab.comMiro: https://miro.comDescript: https://www.descript.comStack Overflow: https://stackoverflow.comChegg: https://www.chegg.comAirbnb: https://www.airbnb.comEthan Mollick: https://www.oneusefulthing.orgPeter Yang: https://creatoreconomy.so/BooksThe Creative Act: https://www.goodreads.com/book/show/60965426-the-creative-actThe Namesake: https://www.goodreads.com/book/show/33917.The_Namesake#productmanagement #PM #atlassianAbout AtlassianBehind every great human achievement, there is a team. We help teams advance humanity through the power of software.
    Show More Show Less
    55 mins
No reviews yet