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/ji...Chapters01:31 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: / four-thousand-weeks 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.

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.