Cemre Güngor has helped shape how billions interact with technology, from Facebook and Instagram's global sharing experiences to Figma's AI-powered workflows, and now reimagining the browser at The Browser Company with Dia.In this conversation, we break down:

• Product Craft in the AI Era
• Why starting with the end in mind matters more than ever when prototyping is democratized
• The difference between durable AI features and "demo candy"
• How to evaluate prototypes without clear problem definition
• Scaling Products Across Surfaces
• What changes (and what doesn't) when building for social platforms vs creative tools vs AI-native workflows
• Why product managers get too attached to their existing mental models
• The hidden costs of ignoring new interaction paradigms
• Real AI Workflows at The Browser Company
• Practical examples: automated communication audits, personality type predictions, and workflow optimization
• Why meeting transcripts are the most underutilized data source in remote work

Jira Product Discovery is the home for all your product ideas, customer feedback, and bets, so you can prioritize what actually matters and share living roadmaps with your stakeholders. Turn scattered requests and spreadsheets into a single, shared source of truth that connects directly to delivery in Jira.

Get it free at https://www.atlassian.com/software/jira/product-discoveryChapters01:31 Welcome back to Product in Practice03:21 Starting with the end in mind and focusing on problems05:36 Product management behavior that stopped working, moving from Instagram to Figma08:30 Shift from metric-driven to judgment-based product management09:18 Cemre's background with AI at Figma10:50 Learning by doing and shipping quickly14:39 How LLM-based features change product development16:59 The Browser Company's focus on design and intentionality19:10 The single most important test for an AI feature: internal usage22:20 How evolving AI models (reasoning models) impact product roadmaps23:03 The Bitter Lesson: When to wait for model improvements25:09 Why agentic workflows (like computer use models) are not a priority yet26:12 The necessity of shipping first to learn what good looks like for general-purpose AI assistants29:22 The browser's responsibility in an AI world: holding all your context32:47 The key value of an AI browser: bringing in your context34:33 Advice for PMs: Do the boring thing with AI37:06 Demo: Simulating your manager's perspective (the "Josh skill")42:18 Demo: Revising a document with real meeting feedback/transcript47:00 Demo: Daily priority recommendations based on all context (Memory, Calendar, Slack)51:09 How AI tools have transformed productivity and PM workflows53:54 Demo: Coaching and feedback on communication style from all channels54:41 The advantage of browser-level integrations like Dia'sReferencedArc Search (mobile app): https://arc.net/search Arc (browser): https://arc.net/ Gemini (model): https://gemini.google.com and https://ai.google.dev/gemini-api/docs... Cursor: https://cursor.com/ Claude Code: https://claude.com/product/claude-code GPT Codex: https://openai.com/codex/ Granola (note-taking tool mentioned): https://www.granola.ai/ Four Thousand Weeks:  https://www.goodreads.com/book/show/54785515-four-thousand-weeksAbout 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.

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

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If you're a PM, designer, or engineer building AI products, this is required viewing for 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.

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 essential

Key takeaways

AI 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 observation

ReferencedReforge: https://www.reforge.com

Magic Patterns: https://www.magicpatterns.com

Claude MCP: https://modelcontextprotocol.io

Smithery: https://smithery.ai

v0: https://v0.app

Lovable: https://lovable.dev

Bolt: https://bolt.new

GitLab: https://gitlab.com

Miro: https://miro.com

Descript: https://www.descript.com

Stack Overflow: https://stackoverflow.com

Chegg: https://www.chegg.com

Airbnb: https://www.airbnb.com

Ethan Mollick: https://www.oneusefulthing.org

Peter 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 #atlassian

About AtlassianBehind every great human achievement, there is a team. We help teams advance humanity through the power of software.

Laura Burkhauser is CEO at Descript, where she's building AI-powered video editing tools that are changing how creators work. She's previously led product at Twitter, Rent the Runway, and The Tote. She's recognized for launching Underlord, Descript's AI co-editor, and expanding what's possible in creator productivity.

Key takeaways:

Don't lead with fear, lead with excitement. Rather than being driven by FOMO and the "burning platform" of AI disruption, discover your "beach moment" - something that genuinely excites you about AI's potential. For Laura, it was successfully shipping an undo button to production using Cursor and Claude. Once you experience that superpower feeling, investing in learning becomes natural.

Start with simulate, then automate, then delegate. Avoid immediately purchasing AI tools or attempting to automate everything. Begin by simulating workflows manually to validate the concept (as Laura did with post-launch tasks). Then build or purchase automation once you've proven it works. Finally, delegate when the system is dependable enough to run with minimal oversight.

Context is the new currency for career advancement. Junior employees previously earned their way into key meetings by creating slides or taking notes - tasks AI now handles. Today's juniors must identify new ways to provide value that leverage their AI-native abilities, gaining access to the context that will make them strategic leaders.

AI won't replace creativity; it amplifies it. In creative workflows, AI isn't about delegation - it's about achieving things you never thought possible. Laura went from creating 30-second clips to producing 30-minute videos. The objective isn't to hand off creative work, but to give creators superpowers to execute their vision more quickly.

Get your whole team to vibe code something. Laura required everyone on her product team to set up Cursor and prototype something they'd wanted to build but couldn't justify resources for. Once designers could handle their own VQA and PMs could ship features independently, the team was fully bought in. The experience of power drives adoption.

Chapters:

00:00 Introduction to Laura Burkhauser
02:00 Laura's path from fashion tech to Descript
05:00 The AI acceptance scale: from hostile to rewired
08:30 Laura's "flipping moment" with Cursor and Claude
12:00 Building AI buy-in across your team
15:00 Translating AI adoption into customer value
18:00 The two-by-two framework: what to do less vs more
22:00 Maintaining quality whilst doubling engineering output
24:00 Responsible AI and voice synthesis ethics
26:00 Advice for PMs starting their careers in the AI era
29:00 Context as the new currency for career growth
31:00 Demo: Automating post-launch workflows
35:00 Using Cursor to generate progress reports
38:00 Creating release notes and change logs with AI
41:00 Building launch kits automatically
45:00 Creating launch videos with Underlord
52:00 AI in creative work vs other workflows
56:00 How AI is changing relationships between PM, PMM, and design
57:00 Quick-fire questions and final thoughts

Referenced:

• Descript: https://www.descript.com

• Underlord: https://www.descript.com/underlord

• Cursor: https://www.cursor.com

• Claude: https://www.anthropic.com

• Whisper Flow: https://wisprflow.ai/

• Runway: https://runwayml.com

Recommended books:

• The Brothers Karamazov: https://www.goodreads.com/book/show/4934.The_Brothers_Karamazov

Where to find Laura Burkhauser:

• LinkedIn: https://www.linkedin.com/in/burkhauser/

• Descript:https://www.descript.com

Where to find Axel Sooriah:

• Newsletter: https://www.axel.pm