Product Growth Podcast

Aakash Gupta
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  • التكنولوجيا
  • مرتان في الأسبوع
Product Growth Podcast

The latest insights into how great products grow, how to be a better PM or product leader, and how to get a PM job. www.news.aakashg.com

  1. قبل ٦ أيام

    The PM’s Role in AI Evals: Step-by-Step

    Today, we’ve got some of our most requested guests yet: Hamel Husain and Shreya Shankar, creators of the world’s best AI Evals cohort. You’ll learn: - Why AI evaluations are the most critical skill for building successful AI products - What common mistakes people are making and how to avoid them - How to effectively "hill climb" towards better AI performance If you're building AI features, or aiming to master how AI Eval actually works, this episode is your step-by-step blueprint. ---- Brought to you by: The AI Evals Course for PMs & Engineers: You get $800 with this link Jira Product Discovery: Plan with purpose, ship with confidence Vanta: Automate compliance, security, and trust with AI (Get $1,000 with my link) AI PM Certification: Get $500 with code AAKASH25 ---- Timestamps: 00:00:00- Preview 00:02:06 - Three reasons PMs NEED evals. 00:04:40 - Why PMs shouldn't view evals as monotonous 00:06:23 - Are evals the hardest part of AI products solved? 00:07:37 - Why can't you just rely on human "vibe checks"? 00:12:11 - Ad 1 (AI Evals Course) 00:13:10 - Ad 2 (Jira Product Discovery) 00:14:06 - Are LLMs good at 1-5ratings? 00:15:45 - The "Whack-a-mole" analogy without evals 00:16:26 - Hallucination problem in emails (Apollo story) 00:21:22 - How Airbnb used machine learning models? 00:23:56 - Evaluating RAG Systems. 00:29:52 - Ad 3 (Vanta) 00:30:56 - Ad 4 (AIPM Certification on Maven) 00:31:42 - Hill Climbing 00:35:51 - Red flag: Suspiciously high eval metrics 00:39:02 - Design principles for effective evals 00:42:42 - How OpenAI approaches evals 00:44:39 - Foundation models are trained on "average taste" 00:49:36 - Cons of fine-tuning 00:51:27 - Prompt engineering vs. RAG vs. Fine-tuning 00:53:00 - Introduction of "The Three Gulfs" framework 00:56:04 - Roadmap for learning AI evals 01:01:41 - Why error analysis is critical for LLMs 01:08:29 - Using LLM as a judge 01:10:15 - Frameworks for systematic problem-solving in labels 01:17:42 - Importance of niche and qualifying clients. (Pro tips) 01:18:43 - $800K for first course cohort! 01:20:15 - Why end a successful cohort? 01:25:49 - GOLD advice for creating a successful course 01:33:39 - Outro ---- Key Takeaways: 1. Stop Guessing. Eval Your AI. Your AI isn’t an MVP without robust evaluations. Build in judgment — or you’re just shipping hope. Without evaluation, AI performance is a happy accident. 2. Error Analysis = Your Superpower. General metrics won’t save you. You need to understand why your AI messed up. Only then can you fix it — not just wish it worked better. 3. 99% Accuracy is a LIE. Suspiciously high metrics usually mean your evaluation setup is broken. Real-world AI is never perfect. If your evals say otherwise, they’re flawed. 4. Fine-Tuning is a Trap (Mostly). Fine-tuning is expensive, brittle, and often unnecessary. Start with smarter prompts and RAG. Only fine-tune if you must. 5. Your Data’s Wild. Understand It. You can’t eyeball everything. Without structured evaluation, you’ll drown in noise and never find patterns or fixes that matter. 6. Models Fail to Generalize. Always. Your AI will break on new data. Don’t blame it. Adapt it. Use RAG, upgrade inputs, and stop expecting out-of-the-box magic. 7. OpenAI Doesn’t Get Your Vibe. Their models are average-taste. Your product isn’t. If you want your brand’s voice in your AI, you must define it yourself — with evals. 8. Trust LLM Judges... but validate them hard. LLMs can scale your evals — but you still need to verify them against human-labeled data. Don’t blindly trust your judge. 9. Your Prompts Are S**T. If your AI is bad, it’s probably your fault. The cheapest, most powerful fix? Sharpen your prompts. Clearer instructions = smarter AI. 10. Let AI Teach You. Seriously. LLM judges aren’t just scoring you — they can teach you. Reviewing how your AI fails is the best way to learn what great outputs should look like. ---- Check it out on Apple, Spotify, or YouTube. ---- Related Podcasts: Complete Course: AI Product Management Tutorial of Top 5 AI Prototyping Tools If you only have 2 hrs, this is how to become an AI PM College Dropout Raised $20M Building AI Tools | Cluely, Roy Lee Bolt CEO and Founder on How he Hit $30M ARR in a Year LogRocket CEO and Founder on How to Build a $100M+ AI Startup Amplitude CEO and Founder on Building the Product Analytics Leader ---- P.S. More than 85% of you aren't subscribed yet. If you can subscribe on YouTube, follow on Apple & Spotify, my commitment to you is that we'll continue making this content better. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

    ١ س ٣٥ د

  2. ٨ يوليو

    AI Product Discovery: Complete Course

    We could talk a million things with Tanguy Crusson but I’m keeping it to what I like the most about his work - Product Discovery. He shares a rare, behind-the-scenes look at how his team at Jira Product Discovery uncovers real user problems, validates solutions quickly, and avoids wasting time on ideas that won’t land. ---- Brought to you by: Jira Product Discovery: Plan with purpose, ship with confidence Product Faculty: Get $500 off the AI PM certification with code AAKASH25 Vanta: Automate compliance, security, and trust with AI (Get $1,000 with our link) AI PM Certification: Get $500 off Miqdad Jaffer (of OpenAI)’s certification ---- Timestamps: Preview & Intro — 00:00:00 Has AI Actually Changed Product Discovery? — 00:00:27 Ad: Jira Product Discovery — 00:10:50 Ad: AIPM Certification with OpenAI PM — 00:11:45 Where AI Truly Helps in Discovery (Real Use Cases) — 00:12:32 Watch the Live Demo on YouTube for Full Context — 00:14:34 The Discovery Process (Deep Dive) Phase 1 – Wonder: How Atlassian Uncovers Real Problems — 00:16:51 Why Tanguy Hasn’t Written a PRD in 5 Years (+ Wild Engineer Story) — 00:21:04 How to Lead Great User Interviews (Tips from a UX Researcher) — 00:25:24 Ad: Vanta Compliance & Security — 00:28:30 Ad: AI Evals for PMs & Engineers — 00:29:34 The Right Way to Structure Discovery Documents — 00:30:34 How Atlassian Actually Uses Tools for Product Discovery (Full Stack Demo) — 00:33:23 Why This System Works Better Than Traditional PM Workflows — 00:41:24 Moving Through Discovery Phase 2 – Explore: Rapid Prototypes & Real Feedback — 00:41:58 Phase 3 – Make: When the Team Commits to Building — 00:49:04 “Just Ship It” is Bad Advice — Here’s Why — 00:52:24 Can You Trust Feedback from Free Users? — 00:56:00 Phase 4 – Impact: Measuring Real-World Results — 01:07:33 How to Build Real Trust as a Product Manager — 01:14:41 PMs Want to Keep Engineers Busy: Good Strategy or Trap? — 01:17:46 Aakash: “I Wish I Talked to You 10 Years Ago”, Here’s Why — 01:22:46 Closing Reflections & Takeaways — 01:26:33 ---- Key Takeaways: 1. Discovery isn’t a phase, it’s a system. Atlassian runs product discovery continuously, not just “before development.” It’s embedded across problem finding, prototyping, building, and post-launch. 2. Use video, not documents, to communicate user pain. Instead of writing long research summaries, PMs compile 10-minute reels of real customer interviews. Watching raw emotion builds urgency and alignment. 3. Start with ~10 users — not thousands. Atlassian validates ideas with small, focused user groups. It's faster, cheaper, and more revealing than wide surveys or launches. 4. Prototype with whatever is fastest. From AI tools like V0 to basic Figma slides, the goal is speed. You don’t need polished UIs — you need fast feedback on core concepts. 5. Strong user reactions guide investment. When users say “I need this now,” that’s a green light. Mild interest or polite nods? That’s a warning to dig deeper. 6. Build only once you have real pull. They don’t move into development (“Make” stage) until a prototype has strong qualitative validation. Code follows conviction. 7. PMs rotate weekly to tag and analyze feedback. Every week, one PM owns triaging incoming feedback, tagging it to ideas, and surfacing themes. Discovery is part of the rhythm — not a side project. 8. Real discovery requires exposure, not summaries. Dashboards, sanitized reports, and secondhand quotes are not enough. PMs must stay close to raw user input — live or recorded. 9. Post-launch reflection is mandatory. Every shipped feature goes into the “Impact” phase. They assess: is it working? Should we scale, refine, or kill it? 10. Discovery is a team sport. PMs, designers, engineers, even sales, everyone participates in interviews, watches clips, and shapes the product. It’s not just a PM’s job. ---- Check it out on Apple, Spotify, or YouTube. ---- Related Podcasts: How ZoomInfo IPO’d - With CEO/ Founder Henry Shuck How LogRocket Became a $100M+ AI Company - With CEO/ Founder Matt Arbesfeld How Amplitude Became the #1 Product Analytics Tool - With CEO/ Founder Spenser Skates How Zoom Took Over The World - With Zoom's Meetings Product during Covid ( now leads their Events & Webinars product) ---- P.S. More than 85% of you aren't subscribed yet. If you can subscribe on YouTube, follow on Apple & Spotify, my commitment to you is that we'll continue making this content better. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

    ١ س ٢٨ د

  3. ٦ يوليو

    This $20M AI Founder Is Challenging Elon and Sam Altman | Roy Lee, Cluely

    Amazon banned him. Ivy Leagues kicked him out. And still, he went mega viral, built a $6M ARR AI startup, and raised $15M from a16z… all in a matter of weeks. This might be the craziest founder story you’ll hear all year. If you’re building in a competitive market, struggling to stand out, or just want to learn how to blend controversy with growth, this one’s for you. ---- Brought to you by: AI PM Certification: Get $500 with code AAKASH25 Jira Product Discovery: Plan with purpose, ship with confidence The AI Evals Course for PMs & Engineers: You get $800 with this link ---- Timestamps: 21yo Worth $100M+ - 0:00 Harvard Kicked Me Out - 3:02 Tech Twitter Main Character - 4:33 Ads - 6:44 Controversial = Views Formula - 8:26 Stripper Commercial Brainstorms - 12:47 Liquid Glass Before Apple - 16:55 User Feedback Drives Product - 19:48 Sales Tech & Enterprise - 23:16 Cheating in Meetings - 27:19 Ad - 28:22 How to Fundraise Like Roy - 29:28 Brain Chips End Game - 31:05 Roy vs Elon vs Sam - 33:12 Frat House Culture - 34:44 The Cluely Internship - 37:37 Are We Getting Dumber? - 38:51 Roy Going to Jail? - 40:44 Thanks for Watching - 42:18 ---- Key Takeaways: 1. Don’t wait for permission. He got kicked out of two top schools and used that energy to build something the world couldn’t ignore. If the system doesn’t reward you, build outside it. 2. Design for real behavior, not rules. Interview Coder wasn’t legal or polite, it was effective. It gave users AI help without getting caught. Start with what people actually want. 3. Rethink how AI should show up. Stop building chatbots. Build experiences where AI quietly blends into the workflow. Think overlays, not windows. Think invisible, not interruptive. 4. Your product doesn’t need to sound safe. “Cheat on everything” wasn’t just a headline, it was a magnet for attention. Don’t fear being bold if it reflects what your product actually does. 5. You don’t need a pitch deck if the story tells itself. Cluely raised $15M without running a process. When the traction is undeniable and your product is everywhere, investors come to you. 6. Build virality into your operating system. Don’t “hope” something goes viral. Study what’s working. Run daily idea sessions. Create with the expectation that every post could hit 100M views. 7. Make your content pass two filters or kill it. Can anyone understand it instantly? Will people feel something strong enough to react? If not, it won’t break through. Keep it simple and emotional. 8. Ignore vanity metrics, chase visibility. Don’t waste time measuring click-through rates on content that won’t work next week. Stay focused on showing up everywhere your user lives. 9. You don’t need a big team to move fast. Cluely runs on 4 engineers. No designers. No PMs. Still they've $6M ARR. If you can ship fast and learn faster, you’re already ahead. 10. Build a product that feels inevitable. This isn’t just for sales teams. Cluely is betting on a world where AI support shows up before you even ask for it. Design for that future now. ---- Check it out on Apple, Spotify, or YouTube. ---- Related Podcasts: Bolt CEO and Founder on How he Hit $30M ARR in a Year LogRocket CEO and Founder on How to Build a $100M+ AI Startup Amplitude CEO and Founder on Building the Product Analytics Leader ---- P.S. More than 85% of you aren't subscribed yet. If you can subscribe on YouTube, follow on Apple & Spotify, my commitment to you is that we'll continue making this content better. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

    ٤٣ من الدقائق

  4. ٢ يوليو

    How Zoom Took Over The World

    Zoom grew from $1B to $4.5B in months - but behind the scenes, it was chaos. Learn how they froze features, scaled product teams, and held the platform together under global pressure from the head of product at Zoom meetings. ---- Brought to you by: Jira Product Discovery: Plan with purpose, ship with confidence The AI Evals Course for PMs & Engineers: You get $800 with this link Product Faculty: Get $500 off the AI PM certification with code AAKASH25 ---- Timestamps: Preview – 00:00:00 How Big Zoom Is – 00:02:12 Simplifying Zoom UX – 00:03:40 From $1 Billion to $4.5 Billion During Covid - 00:04:38 The Three-Month Feature Freeze Story – 00:06:38 Aakash Shares His Zoom Fortnite Concert Story – 00:07:30 Advice for Product Leaders Facing Hypergrowth – 00:09:25 Ad 1 (Jira) – 00:11:29 Ad 2 (AI Evals Course) – 00:12:43 One Thing He Would’ve Done Differently in His Career – 00:13:25 Handling Zoom's Overvaluation, Layoffs, and Stock Price Drops – 00:14:20 Future of AI in meetings - 00:16:09 Zoom’s Shift into Broadcast and Events – 00:18:55 Why Send a Meeting When You Could Record a Loom? – 00:21:35 Can Zoom Catch AI Avatar Doing Interview - 00:26:23 Ad 3 (AIPM Course) – 00:28:11 Using Zoom Like a Pro – 00:28:58 Cool Things About the AI Companion – 00:32:27 Balancing Simplicity While Shipping Great Features – 00:36:37 How PMs Can 10x Their Meeting Management – 00:40:42 How to Get Hired at Zoom – 00:44:56 What’s Unique About How Zoom Builds Products – 00:51:35 Lessons Learned from Running QBRs – 00:54:18 Culture at Zoom: Metrics Driven or Not - 00:57:03 Zoom Team Adopting Prototyping Tools? – 00:58:53 Outro – 01:00:17 ---- Key Takeaways: 1. Zoom didn’t just scale, it survived a once-in-a-generation demand shock. In early 2020, Zoom grew from $1B to $4.5B revenue and added 180+ PMs in months. To stay afloat, they froze all feature development for 3 months and focused solely on stability, security, and critical user needs. 2. Most teams drown in feature requests. Zoom built a triage system. He created structured buckets to track thousands of bugs, asks, and UI issues. This wasn’t just project management. It was the only way to maintain control during chaos. 3. The best PMs don’t just fix, they find the root cause. Instead of reacting to symptoms, he emphasized thinking a layer deeper. What assumption broke? What system failed? Root cause thinking kept Zoom from wasting time on surface-level patches. 4. Simplicity beats novelty even in billion-dollar products. Zoom’s team went deep on seemingly minor features like “Raise Hand.” They reworked ordering logic, host controls, and UX friction points, because good meetings are built on small, invisible wins. 5. Zoom is no longer just meetings, it’s becoming a media platform. From live webinars to pro events, Zoom is building for marketers, educators, and producers. Tools like Zoom Events, Production Studio, and broadcast integrations are reshaping how large-scale communication happens. 6. AI is Zoom’s next act and it’s already driving behavior change. The AI Companion generates instant meeting summaries, action items, and catch-up flows. Internally, teams rely on it heavily — and Beckmann calls it Zoom’s most impactful feature post-COVID. 7. Async isn’t the end of meetings, it’s a better tool for the right job. After stepping away from meetings, John personally built Zoom Clips. It’s not here to replace meetings — but for product updates, specs, and visual explanations, async is more efficient and respectful. 8. AI avatars aren’t hype, they solve a very real problem. When you're triple-booked with no breaks, avatars offer psychological relief - for both you and the people in the room. Better than being just another muted black screen. 9. During layoffs, product leaders become morale managers. In 2023, John had to deliver tough news to his team. His stance: be honest, coach through uncertainty, and remind people that companies aren’t families, they’re teams. Your job is to build trust, not give false comfort. 10. Want to stand out in a Zoom interview? Be human, not a highlight reel. Zoom hasn’t seen major AI cheating issues, yet. But John says authenticity matters more than polish. Don’t recite perfect answers. Speak like a real person who’s been in the work, solved real problems, and understands the platform. ---- Check it out on Apple, Spotify, or YouTube. ---- Where to Find John: LinkedIn: John Twitter: Beckmania ---- Related Podcasts: How ZoomInfo Grows: The Story, Growth Motion, and Product Strategy with CEO and Founder Henry Shuck 15 Steps to Build a $100M+ AI Company (From Someone Who Has Done It) - With the Founder & CEO of AI Startup LogRocket, Matt Arbesfeld ---- Up Next I hope you enjoyed the last episode with Aman Khan (It was not less than a AI PM Crash Course where we dove into 5 key AI PM skills). Up next, we have episodes with: Dan Olsen - Author, Lean Product Playbook Tanguy Crusson - Head of Product, Jira Product Discovery Hamel Husain and Shreya Shankar - Hamel Husain: ML Engineer, 20 years in AI; Shreya Shankar: PhD; building DocETL Finally, check out my latest deep dive if you haven’t yet: The Playbook to Land Your First PM Job. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

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  5. ٢٩ يونيو

    What I Learned From Filming 80 Podcast Episodes

    Starting this podcast wasn’t an easy decision. It takes up nearly half my time. And for months, it wasn’t making any money. But fast forward to today, and the podcast is now profitable and central to my creator business. So I did something different this week. I recorded a solo episode breaking down everything I’ve learned: - How I built and monetized a niche podcast - The exact growth engine that powers the show today - Some killer AI workflows I’ve learned for your job search and PM job ---- Brought to you by: Miro: The innovation workspace is your team’s new canvas The AI Evals Course for PMs & Engineers: You get $800 with this link Linear: Plan and build products like the best Product Faculty: Get $500 off the AI PM certification with code AAKASH25 ---- Timestamps: Part 1: How I Built and Monetized a Niche Podcast 0:00 - Exponential Growth Finally Happening 1:21 - How I Grew This Podcast 4:31 - Learning From 80 Episodes 8:46 - How Podcasts Make Money 10:50 - My Dream Job: OpenAI Part 2: Breaking Into Product Management & Career Growth 13:36 - Roadmap to Becoming a Product Manager 14:05 - Why 2025 is Great For PMs 21:22 - AI PM Skills Roadmap 23:02 - Finding Your First Paying Customer 26:12 - Zero to 250K Followers Strategy 32:21 - LinkedIn $525K Salary Jump 34:24 - High-Effort Content Strategy 38:05 - Newsletter Success Stack Rank Part 3: Getting PM Jobs & Career Advice 40:51 - Presenting Soft Skills on Resume 42:46 - Breaking Into US PM Jobs (International Students) 46:08 - Is Product Management Right For Me? 49:54 - Time Management & Prioritization Mistakes 52:15 - MBA to PM Roadmap 55:41 - Finding the Right Mentors 57:56 - Sprint Prioritization Framework 59:39 - Detecting Product Passion vs Money Focus 1:01:41 - Platform & AI Product PRDs 1:04:09 - Product Management Beliefs That Changed 1:05:41 - Newsletter Revenue & Churn Management 1:07:02 - Time Management & Focus Strategies 1:09:07 - Common Misconceptions About Content Creators ---- Key Takeaways: 01 — Podcast Turnaround This podcast is now passing 50K listeners per episode, 11K subscribers on YouTube, and has become central to my creator business. The exponential growth kicked in around episode 80 after consistent investment and improvement. 02 — Quality Over Equipment Obsessing over microphones, cameras, and lighting hits diminishing returns fast. The real growth came from improving trailers, clip selection, and backing off endless equipment upgrades to focus on profit generation. 03 — Creator Time Investment The podcast now consumes 50% of my time but generates significant monthly profit. Success required treating it as a long-term experiment, reinvesting everything for 50+ episodes before expecting returns. 04 — Content Platform Strategy Start with LinkedIn until 10K followers, then add YouTube, then Twitter at 100K, then Medium at 1M. Master one platform completely before spreading to the next for maximum growth efficiency. 05 — AI Prototyping Revolution Product managers can now build functional prototypes in minutes. Using Gemini 2.5 Pro for PRDs and Bolt.new for development, I built Apple Podcasts video features from strategy to clickable prototype in under 10 minutes. 06 — Resume AI Mastery Gemini 2.5 Pro dominates resume customization, beating all other models. What used to take 15 minutes of manual customization now takes 80 seconds with better results using proper context and prompting techniques. 07 — PM Job Security 2025 is an excellent time to enter product management. 75% of PM work involves people coordination and stakeholder alignment that AI cannot replace, making it as secure as doctor/lawyer/engineer careers. 08 — Career Switching Strategy Use your domain expertise as an edge — become a product analyst first, then transfer internally, or target companies building tools for your previous industry. Take the level down initially but leverage your customer knowledge. 09 — PM Strategy Focus Stop being the design-engineering glue person. Your core identity should be product strategy, business metrics, and stakeholder management. Empower teams to answer their own questions while you influence at higher levels. 10 — Platform Product PRDs Building for developers requires two-step user stories — what developers need from your platform, and what end users need from their products. Include API calls, uptime metrics, and governance considerations in your requirements. ---- Check it out on Apple, Spotify, or YouTube. ---- Related Podcasts: Growing to 125K+ on LinkedIn and Cracking B2B Content with Pierre Herubel How to Win on TikTok and Medium with Professor Aaron Dinin, 100K+ on each How I Wrote 3 of My Biggest LinkedIn Posts ---- P.S. More than 85% of you aren't subscribed yet. If you can subscribe on YouTube, follow on Apple & Spotify, my commitment to you is that we'll continue making this content better. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

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  6. ٢٠ يونيو

    The Lean Product Playbook 10 Years Later: Product Management in the Age of AI

    Product management fundamentals are timeless. But the tools? Completely transformed. Every PM needs to master new workflows in 2025: AI Prototyping - From text to live prototype in minutes Design Collaboration - Working with designers in the AI age User Research - Systematic validation that actually works Problem Definition - The only bottleneck that matters Team Dynamics - Escaping the "Jira jockey" trap So, in today's episode, I bring you the definitive guide to product management in the AI era: I’ve teamed up with Dan Olsen - author of The Lean Product Playbook and one of the most respected voices in product management for over 15 years. Dan has seen it all: from the early days at Intuit to consulting with hundreds of startups. He's been through the internet wave, mobile wave, and now the AI wave. ---- Brought to you by: WorkOS: Your app, enterprise ready Jira Product Discovery: Plan with purpose, ship with confidence The AI Evals Course for PMs & Engineers: You get $800 with this link Product Faculty: Get $500 off the AI PM certification with code AAKASH25 ---- Timestamps: Introduction - 0:00 Lean Product Playbook Origins - 1:49 AI's Real Impact on PMs - 3:44 The Prototyping Revolution - 5:18 Ads - 12:02 Solution Space Risks - 14:18 When Designers Become Bottlenecks - 22:49 AI Tool Recommendations - 26:37 Ads - 32:21 Design Process Evolution - 34:07 User Research Hierarchy - 42:32 Testing Methods Explained - 44:34 Running User Sessions - 53:05 Avoiding Interview Mistakes - 1:01:15 Systematic Feedback Capture - 1:03:23 Escaping Jira Jockey Trap - 1:08:46 Current BS Trends - 1:11:55 Dan's Revenue Breakdown - 1:13:34 Where to Find Dan - 1:18:33 ---- Key Takeaways: 1. AI hasn't changed the fundamentals. You still need to understand customers, identify problems, and prioritize opportunities. AI can't tell you about your customers or validate market needs for you. 2. Prototyping is the biggest unlock. What used to take weeks (text → sketches → wireframes → Figma → code) now happens in minutes (text → live prototype). This is where AI truly transforms PM work. 3. Start with Lovable/Bolt, graduate to Cursor. Lovable and Bolt are perfect for quick prototyping without code. Cursor gives you more control and learning opportunities for serious AI PMs willing to touch code. 4. The design gap is closing. AI tools have moved every team up 1-2 levels in UX maturity. Teams without designers can now create professional prototypes, but still need humans for breakthrough innovation. 5. Match research method to uncertainty. New product/market = in-person research. Existing product usability = remote unmoderated. The more uncertain you are, the more human interaction you need. 6. Use the three-bucket system. Categorize all user feedback into: Feature Set, UX Design, and Messaging. Test in waves of 5-8 users, track percentages, fix issues, repeat. 7. Good usability ≠ product-market fit. Always ask "How likely are you to use this?" at the end. Dan learned this the hard way - zero complaints doesn't mean people want your product. 8. Protect discovery time. If your PM-to-dev ratio is above 1:8, you're probably a Jira jockey. Use Dan's 4 D's: Discover → Define → Design → Develop. Spend meaningful time in all four. 9. Collaborate, don't replace designers. Be upfront: "This prototype is directional, not pixel-perfect." Use AI for quick validation, bring designers in for differentiated experiences and innovation. 10. Stop sprinkling AI everywhere. AI is a solution looking for problems. Start with real customer pain points, then figure out if AI solves them better than existing approaches. ---- Check it out on Apple, Spotify, or YouTube. ---- Where to Find Dan: Book Website YouTube Lean Product Meetup ---- Related Podcasts: Tutorial of Top 5 AI Prototyping Tools Complete Course: AI Product Management We Built an AI Agent to Automate PM in 73 mins (ZERO CODING) We Built an AI Product Manager in 58 mins (Claude, ChatGPT, Loom + Notion AI) We Built an AI Employee in 62 mins (Cursor, ChatGPT, Gibson, Crew AI) ---- Up Next I hope you enjoyed the last episode with Tom Occhino (where we gave an in-depth v0 tutorial). Up next, we have episodes with: John Beckmann - Head of Events + Webinars, Zoom Tanguy Crusson - Head of Product, Jira Product Discovery Hamel Husain and Shreya Shankar - The 2 Experts in AI Evals Finally, check out my latest deep dive if you haven’t yet: The Playbook to Land Your First PM Job. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

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  7. ١٥ يونيو

    AI PM Crash Course: Prototyping → Observability → Evals + Prompt Engineering vs RAG vs Fine-Tuning

    Every PM has to build AI features these days. And with that means a completely new skill set: - AI prototyping - Observability, Akin to Telemetry - AI Evals: The New PRD for AI PMs - RAG v Fine-Tuning v Prompt Engineering - Working with AI Engineers So, in today’s episode, I bring you a 2-hour crash course into becoming a better AI PM. I’ve teamed up with Aman Khan. When it comes to people creating AI PM content, Aman Khan is amongst the most insightful and informed. And that's because he's been an AI PM since 2019: - He worked at Cruise on self-driving cars. - He's worked with Spotify on their AI systems. - And now he works at Arize, one of the leading observability and evals companies. ---- Brought to you by: Miro: The innovation workspace is your team’s new canvas Jira Product Discovery: Plan with purpose, ship with confidence Maven: Get $100 off Aman’s course with my code ‘AAKASHxMAVEN’ Amplitude: Test out the #1 product analytics and replay tool in the market ---- Timestamps: Can Anyone Become AIPM? - 0:00 5 AIPM Skills Overview - 5:52 Skill 1: AI Prototyping - 6:31 Ad: Miro - 13:35 Ad: Atlassian - 14:50 Building Trip Planner Agent - 15:27 Ad: Maven - 29:46 Ad: Amplitude - 30:40 Skill 2: Observability - 50:34 Skill 3: Evals - 1:10:10 RAG vs Fine-Tuning vs Prompt Engineering - 1:29:54 Bolt Teardown - 1:30:32 Skill 5: Working With Engineers - 1:43:24 Don't Make These Mistakes - 1:48:33 2 Hours Weekly Plan - 1:53:55 AIPM Jobs Exist - 1:57:45 Aman's Resources - 2:00:48 Outro - 2:04:00 ---- Key Takeaways: 1. Cursor beats Bolt for serious AI PMs. While Bolt is great for quick mockups, Cursor gives you the control you need to build real agent systems and understand what's happening under the hood. 2. Observability comes before evals. Just like regular products need telemetry for analytics, AI products need traces for evals. Point Cursor to documentation and it adds what you need. 3. Vibe coding doesn't scale. Looking at outputs and deciding if they "feel good" works for prototypes, but not production. You need systematic evals to measure what "good" actually means. 4. Most PMs fine-tune too early. Aman showed a prompt outperforming a fine-tuned model. Start with prompting (95% of results), add RAG for external data, only fine-tune for cost/speed. 5. Your evals need evals. When your LLM judge marks outputs as "friendly" while your human labels say "robotic," that mismatch tells you exactly where to improve your system. 6. Use text labels, not numbers. LLMs understand "friendly vs robotic" better than 1-5 scales. They're trained on language, not mathematics. 7. AI engineers want data, not docs. Stop sending Google Docs with requirements. They want you labeling datasets and defining success through evals. 8. Bolt is just a really good prompt. Aman tore down Bolt's architecture - it's system prompts + tool calling + code generation. The "magic" isn't magic. 9. Side projects are your interview hack. When Aman asks "What are you building?" he can immediately gauge curiosity, initiative, and hands-on experience. 10. Don't automate yourself too early. Use AI as a second brain for analysis, but don't try to automate your entire job. Learn to work with reasoning models to push your thinking. ---- Check it out on Apple, Spotify, or YouTube. ---- Where to Find Aman: LinkedIn: Aman Khan X: Aman Khan Substack: aiproductplaybook.com Company: Arize Course: The AI PM Playbook ---- Related Podcasts: Tutorial of Top 5 AI Prototyping Tools Complete Course: AI Product Management We Built an AI Agent to Automate PM in 73 mins (ZERO CODING) We Built an AI Product Manager in 58 mins (Claude, ChatGPT, Loom + Notion AI) We Built an AI Employee in 62 mins (Cursor, ChatGPT, Gibson, Crew AI) ---- Up Next I hope you enjoyed the last episode with Tom Occhino (where we gave an in-depth v0 tutorial). Up next, we have episodes with: Dan Olsen - Author, Lean Product Playbook John Beckmann - Head of Events + Webinars, Zoom Tanguy Crusson - Head of Product, Jira Product Discovery Finally, check out my latest deep dive if you haven’t yet: The Playbook to Land Your First PM Job. ---- If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

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  8. ١١ يونيو

    Behind v0 (Top AI Prototyping Tool): Tutorial and Story from the CPO

    “My whole Product, design, and engineering team has v0 licenses.” That’s what Jeremy Epling, CPO at Vanta, said in a recent episode. So, I went straight to the source. I sat down with the CPO of Vercel to unpack why v0 is becoming the tool for modern product and engineering teams alongside vibe coders. We cover: - The future of AI prototyping for PMs and designers - How v0 builds product - A full tutorial of v0 Whether you’re a PM trying to stay ahead, a founder rethinking velocity, or a builder curious about what’s next, this episode is for you. Brought to you by: WorkOS: Your App, Enterprise Ready Jira Product Discovery: Build what matters to business and users The AI Evals Course for PMs & Engineers: You get $800 with this link. Product Faculty: Get $500 off the AI PM certification with code AAKASH25 Timestamps: Preview – 00:00:00 The Agenda – 00:01:07 Live Demo 1: Cloning LinkedIn Newsfeed – 00:03:01 Live Demo 2: Personalized Apollo Homepage (Based on User Behavior) – 00:04:50 Ad 1: WorkOS – 00:09:50 A d 2: Jira Product Discovery – 00:11:O2 LinkedIn Demo Continued – 00:11:58 Live Demo 3: Grok-Powered Post Composer – 00:14:04 What He’s Building with v0 – 00:15:34 The Feature Factory Problem – 00:24:16 Team Size Behind v0 – 00:27:25 Ad 3: AI Evals Course by Hamel & Shreya – 00:29:39 Ad 4: AI PM Course by Product Faculty – 00:30:39 Team Size Behind Vercel – 00:31:26 Competing with Bolt, Lovable, Replit & Others – 00:34:18 His Reflections on Creating React – 00:35:39 Demo Updates and What’s Changed – 00:37:57 How Vercel Builds Products – 00:43:45 How v0 Team Uses v0 Internally – 00:48:37 How PMs Should Think About Prototyping – 00:50:26 From Integration Idea to Shipped Feature: Thought Process – 00:53:04 Buying v0 Licenses for the PM Team – 00:57:37 His Journey: From Engineer to CPO – 00:59:32 How He Landed the CPO Role at Vercel – 01:03:56 The Future of AI for PMs – 01:11:19 Closing Thoughts – 01:14:37 Key Takeaways 1. The prototype is the new PRD. You don’t need a 5-page document to explain an idea anymore. A working prototype - even if imperfect - communicates 10x more. And with tools like v0, you can build one in minutes. 2. Building speed doesn’t eliminate the need for strategy, it amplifies it. When anyone can ship, the most important job becomes deciding what’s worth building. Product discernment is more valuable than ever. 3. v0 isn’t just for engineers. Designers, PMs, and even salespeople are now building working apps without touching code. The line between "builder" and "non-builder" is disappearing. 4. Internal use cases drive innovation. The most successful v0 features didn’t come from competitive analysis, they came from real internal needs. If it solves your own team’s pain, it’ll likely solve others’. 5. Prototyping is now a cross-functional superpower. PMs can validate hypotheses instantly. Designers can test flows without waiting on devs. Sales can create tools for prospects on the fly. Every role levels up when they can build. 6. Fast iteration doesn't mean reckless shipping. The team behind v0 deliberately avoids becoming a “feature factory.” Speed is a tool, not a reason to skip prioritization or problem framing. 7. Your first user is you. This is the core ethos behind v0. If your own team doesn’t use the thing you’re building, something’s wrong. Internal conviction leads to better external adoption. 8. AI won’t be a separate feature, it’ll be the fabric. In the near future, no one will ask “What’s your AI roadmap?” It’ll just be how products get built, used, and improved - quietly running underneath everything. 9. Small teams can ship big things. The v0 team is under 14 people, yet they’ve built a tool that’s enabling thousands to build faster. Size is no longer a limiting factor — clarity and leverage are. 10. The future of product roles is hybrid. Expect to see more design-engineers, PM-builders, and AI-augmented contributors. Tools like v0 are collapsing boundaries — and giving everyone a chance to ship. Check it out on Apple, Spotify, or YouTube. Where to Find Tom LinkedIn: Tom Website: www.tomocchino.com Company: vercel v0: v0.dev Related Podcasts: Tutorial of Top 5 AI Prototyping Tools Complete Course: AI Product Management We Built an AI Agent to Automate PM in 73 mins (ZERO CODING) We Built an AI Product Manager in 58 mins (Claude, ChatGPT, Loom + Notion AI) We Built an AI Employee in 62 mins (Cursor, ChatGPT, Gibson, Crew AI) Up Next I hope you enjoyed the last episode with Brett (where we discussed how he built a $2M/y one person productized agency and how you can too). Up next, we have episodes with: Aman Khan - AI PM @ Arize AI, Spotify, Cruise John Beckmann - Head of Meetings Product, Zoom Tanguy Crusson - Head of Product, Jira Product Discovery Finally, check out my latest deep dive if you haven’t yet: AI Evals: Everything You Need to Know to Start. If you want to advertise, email productgrowthppp at gmail. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.news.aakashg.com/subscribe

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The latest insights into how great products grow, how to be a better PM or product leader, and how to get a PM job. www.news.aakashg.com

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    Aakash Gupta
  • سنوات النشاط
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    © Aakash Gupta
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