Podcast
The Growth Podcast
Hosted by Aakash Gupta · EN
Join 500K+ for deep dives on AI + product management. After spending a decade plus in product, I now interview PM's most insightful experts.
www.news.aakashg.com
www.news.aakashg.com
48episodes
Episodes
Newest firstAll episodes
How to Build ChatGPT Apps (The Next App Store?) | Live Demo by Colin Matthews
Jan 2201:02:22Summary readyThis is a free preview of a paid episode. To hear more, visit www.news.aakashg.comToday’s EpisodeChatGPT Apps might be the next billion-dollar opportunity.Or they might be another ChatGPT feature that gets abandoned in 6 months.I genuinely don’t know yet.But when people say “this could be the new App Store,” my ears perk up. I spent four years building an iOS app in the early days of the App Store. The distribution was incredible. We grew fast purely because of where we were.So when OpenAI announced the ChatGPT App Store, I needed to understand it.I brought in Colin Matthews to break it down. Colin is one of my go-to sources for technical product topics. Our AI prototyping collaborations have been some of your favorite episodes.Today, we’re exploring ChatGPT Apps and what they mean for you as a product builder.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Maven: Get $500 off with my code on Coil Build ChatGPT Apps course* Vanta: Automate compliance, Get $1,000 with my link* Land PM job: 12-week experience to master getting a PM job* Mobbin: Discover real-world design inspiration* NayaOne: Airgapped cloud-agnostic sandbox----If you want access to my AI tool stack - Dovetail, Arize, Linear, Descript, Reforge Build, DeepSky, Relay.app, Magic Patterns, and Mobbin - for free, grab Aakash’s bundle.Are you searching for a PM job? Join me + 29 others for an intensive 12-week experience to master getting a PM job. Only 23 seats left.----Key Takeaways:1. ChatGPT apps = MCP + widgets - The Model Context Protocol (invented by Anthropic) lets AI agents call external tools. OpenAI added UI widgets on top to create embedded app experiences directly in chat.2. 900M weekly active users = massive distribution opportunity - This is the new SEO. Early data shows 26% higher conversion from AI traffic vs traditional search. Every enterprise will eventually build here.3. You're building for multiple platforms - MCP works across ChatGPT, Claude (coming soon), Cursor, and other AI tools. Build once, distribute everywhere. Gemini doesn't support it yet.4. Apps get called based on tool descriptions - Your metadata matters. Like SEO but for LLMs. Run evals to test if correct prompts trigger your tools. Iterate on descriptions to improve discovery.5. Three eval categories: direct, indirect, negative - Direct: user names your app. Indirect: user describes outcome. Negative: irrelevant request shouldn't trigger your tool. Test all three systematically.6. PMs should prototype but engineers ship production - Use tools like Chippy to prototype quickly and test concepts. Show stakeholders real interactions. Engineering team builds the production version.7. Enterprise-first, solo builders second - Large companies (Target, Uber, Canva) are early adopters chasing distribution. But huge opportunity for indie builders once public marketplace launches.8. Best opportunities: embedded collaboration tools - Spreadsheets, task lists, whiteboards where ChatGPT can partner with you. Not just search results—actual interactive experiences.9. Error analysis on observability logs is critical - Track what prompts triggered which tools with what parameters. Look for mismatches between expected and actual behavior. Iterate tool descriptions.10. Marketplace launching by end of 2024/early 2025 - Currently only launch partners can publish. Public marketplace coming soon means anyone can ship apps and reach ChatGPT's massive user base.----Where to Find Colin* LinkedIn* NewsletterRelated ContentNewsletters:* AI Prototyping Tutorial* How to Build AI Products* AI Product Strategy* Complete Course: AI Product ManagementPodcasts:* AI Prototyping for PMs* How to Become an AI PM* Everything You Need to Know About AI----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!If you want to advertise, email productgrowthppp at gmail.
Summary
The PM’s Role in AI Evals: Step-by-Step
Jul 11, 2025Summary readyToday, 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 performanceIf 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 linkJira Product Discovery: Plan with purpose, ship with confidenceVanta: 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- Preview00:02:06 - Three reasons PMs NEED evals.00:04:40 - Why PMs shouldn't view evals as monotonous00:06:23 - 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 evals00:16:26 - 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 Climbing00:35:51 - Red flag: Suspiciously high eval metrics00:39:02 - Design principles for effective evals00:42:42 - How OpenAI approaches evals00:44:39 - Foundation models are trained on "average taste"00:49:36 - Cons of fine-tuning00:51:27 - Prompt engineering vs. RAG vs. Fine-tuning00:53:00 - Introduction of "The Three Gulfs" framework00:56:04 - Roadmap for learning AI evals01:01:41 - Why error analysis is critical for LLMs01:08:29 - Using LLM as a judge01:10:15 - Frameworks for systematic problem-solving in labels01:17:42 - 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 course01:33:39 - 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 ManagementTutorial of Top 5 AI Prototyping ToolsIf you only have 2 hrs, this is how to become an AI PMCollege Dropout Raised $20M Building AI Tools | Cluely, Roy LeeBolt CEO and Founder on How he Hit $30M ARR in a YearLogRocket CEO and Founder on How to Build a $100M+ AI StartupAmplitude 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
Summary
The Lean Product Playbook 10 Years Later: Product Management in the Age of AI
Jun 20, 2025Summary readyProduct 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 minutesDesign Collaboration - Working with designers in the AI ageUser Research - Systematic validation that actually worksProblem Definition - The only bottleneck that mattersTeam Dynamics - Escaping the "Jira jockey" trapSo, 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 readyJira Product Discovery: Plan with purpose, ship with confidenceThe AI Evals Course for PMs & Engineers: You get $800 with this linkProduct Faculty: Get $500 off the AI PM certification with code AAKASH25----Timestamps:Introduction - 0:00Lean Product Playbook Origins - 1:49AI's Real Impact on PMs - 3:44The Prototyping Revolution - 5:18Ads - 12:02Solution Space Risks - 14:18When Designers Become Bottlenecks - 22:49AI Tool Recommendations - 26:37Ads - 32:21Design Process Evolution - 34:07User Research Hierarchy - 42:32Testing Methods Explained - 44:34Running User Sessions - 53:05Avoiding Interview Mistakes - 1:01:15Systematic Feedback Capture - 1:03:23Escaping Jira Jockey Trap - 1:08:46Current BS Trends - 1:11:55Dan's Revenue Breakdown - 1:13:34Where 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:BookWebsiteYouTubeLean Product Meetup----Related Podcasts:Tutorial of Top 5 AI Prototyping ToolsComplete Course: AI Product ManagementWe 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 NextI 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, ZoomTanguy Crusson - Head of Product, Jira Product DiscoveryHamel Husain and Shreya Shankar - The 2 Experts in AI EvalsFinally, 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
Summary
AI PM Crash Course: Prototyping → Observability → Evals + Prompt Engineering vs RAG vs Fine-Tuning
Jun 15, 2025Summary readyEvery 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 EngineersSo, 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 canvasJira Product Discovery: Plan with purpose, ship with confidenceMaven: 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? - 0:005 AIPM Skills Overview - 5:52Skill 1: AI Prototyping - 6:31Ad: Miro - 13:35Ad: Atlassian - 14:50Building Trip Planner Agent - 15:27Ad: Maven - 29:46Ad: Amplitude - 30:40Skill 2: Observability - 50:34Skill 3: Evals - 1:10:10RAG vs Fine-Tuning vs Prompt Engineering - 1:29:54Bolt Teardown - 1:30:32Skill 5: Working With Engineers - 1:43:24Don't Make These Mistakes - 1:48:332 Hours Weekly Plan - 1:53:55AIPM Jobs Exist - 1:57:45Aman's Resources - 2:00:48Outro - 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 KhanX: Aman KhanSubstack: aiproductplaybook.comCompany: ArizeCourse: The AI PM Playbook----Related Podcasts:Tutorial of Top 5 AI Prototyping ToolsComplete Course: AI Product ManagementWe 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 NextI 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 PlaybookJohn Beckmann - Head of Events + Webinars, ZoomTanguy Crusson - Head of Product, Jira Product DiscoveryFinally, 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
Summary
Model Context Protocol (MCP), clearly explained and why it matters
Apr 1, 2025Tap to summarizeThis is wild!Bryan Helmig LIVE shows how to turn AI models into real agents using MCP and Zapier to send Slack messages, draft emails, and automate workflows without writing a single line of code.-Brought to you by:Amplitude: Try their 2-minute assessment of your company’s digital maturityMaven: Get $100 off their courses with code AAKASHxMAVENProduct Faculty: Get $500 off the AI PM certification with code AAKASH25In this episode:Why Should People Watch This Podcast – 00:00:00Ads – 00:01:34What is MCP (Model Context Protocol) – 00:03:03Does MCP Only Work with Anthropic? – 00:04:33Why Zapier’s Take on MCP Matters – 00:05:43Live Demo 1: AI Agent Sends Slack Message via MCP – 00:07:52The Real Limitations of MCP and LLMs – 00:11:27Live Demo 2: ChatGPT Drafts Gmail Replies Automatically – 00:15:56Live Demo 3: Claude-Powered Slack Bot That Responds with Jokes – 00:23:18Ad – 00:30:06Why AI Needs Structure (Not Freeform Outputs) – 00:30:53How Zapier Builds AI Features for the Real World – 00:31:54How Zapier Structures Teams Around AI Work – 00:36:28Zapier’s Culture of Fast AI Prototyping – 00:39:03-Where to Find BryanLinkedInZapierZapier AI agentsZapier MCP-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-I hope you enjoyed the last episode with Lewis Lin (where we discussed how to nail Product Management Interviews). Up next, we have episodes with:Kate Syuma - Ex. Head of Growth Design at MiroDavid Pereira - Author of Untrapping Product TeamsDr. Bart Jaworski - Senior PM, 125K+ on LinkedInI’m so excited to share them with all of you. 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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PM is Dead. So Now What? | The Claire Vo Episode
Mar 4, 2025Tap to summarize3x Chief Product Officer (Currently LaunchDarkly, Formerly Color & Optimizely) Claire Vo has built a 6-figure AI side hustle. In this episode, she expands on the death of the PM role and how she's done it.-Brought to you by:GibsonAI: Your AI Database EngineerMaven: I’ve just launched my unique curation of their top coursesVanta: Automate compliance, manage risk, and prove trust-We're covering:Why Product Management is Dead – 00:00:00Ad – 00:04:37Scope of AI in the PM Role – 00:07:04Limitations of AI in the PM Role – 00:10:42The Role of PMs in Other Fields – 00:13:08Future Trajectory for the Number of PMs – 00:17:28Key Areas for PMs to Adapt in the AI Era – 00:20:12Resources for Improving PM Skills – 00:23:52A PM’s Day: Two Years Ago vs. Two Years From Now – 00:27:50The PM Role at LaunchDarkly – 00:31:11Expectations from a PM – 00:34:19Ad – 00:36:57Future Reporting Structure for PMs – 00:40:21The Death of PMs for VPs and CPOs – 00:42:48ChatPRD tutorial – 00:46:54AI Product Development – 00:57:23Advice for Building a Six-Figure Side Hustle – 01:02:37Q&A: Building an AI Product – 01:08:13A Day in Claire's Life – 01:09:16-Where to find Claire:LinkedInChatPRDTwitter (X)-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-I hope you enjoyed the last episode with Colin Mathews (where we dived deep into 5 top AI tools tutorials). Up next, we have episodes with:April Dunford (Marketing Expert and Author, Obviously Awesome)Eric Simons (CEO and Founder, Bolt)Gayle McDowell ( Author, Cracking the PM Interview)I’m so excited to share them with all of you. 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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Tutorial of Top 5 AI Prototyping Tools: Bolt, Lovable, v0, Replit, and Cursor
Feb 28, 2025Tap to summarizeYou have no idea what’s coming; this isn’t just another talk about AI prototyping. We’re building an app with features, live, right in this podcast. Yes, LIVE.-Brought to you by:GibsonAI: Your AI Database EngineerVanta: Automate compliance, manage risk, and prove trustMaven: I’ve just launched my unique curation of their top courses-We're covering:The Role of AI Prototyping – 00:02:37Step-by-Step AI Prototyping Walkthrough – 00:04:54Writing a PRD for AI-Powered Prototyping – 00:10:05Integrating AI Prototyping with Existing Products – 00:13:58Leveraging LLMs for Planning & Execution – 00:17:19Optimizing the Scope of a Single AI Request – 00:19:51Using Natural Language Prompts Effectively – 00:23:02Validating & Testing AI-Generated Prototypes – 00:26:25Exploring the AI Prototyping Tool Landscape – 00:28:52How PMs Can Integrate AI Prototyping in Daily Workflows – 00:31:36Enhancing the End-to-End Discovery Process with AI – 00:34:37Building AI-Driven Sequences for Apollo – 00:36:29Debugging AI-Generated Prototypes – 00:41:31Getting Feedback: Seeing vs. Reading in PRD – 00:45:42AI-Assisted Design Walkthrough in Figma – 00:48:44Optimizing Workflows for User Research Teams – 00:51:48Extracting Data Insights from Your AI-Generated Design – 00:54:54When Do Database Changes Become Necessary? – 00:56:19Fixing Navigation Issues in AI-Generated Prototypes – 00:58:07Measuring the ROI of AI-Driven Prototyping – 01:00:32Starting from Scratch: AI Prototyping in Replit – 01:03:00Managing AI Tool Crashes Due to Complexity – 01:07:19Handling LLM Struggles with Context Retention – 01:09:24Publishing Your AI-Generated Prototype – 01:13:31-Where to find ColinLinkedInMaven CourseFree AI Prototyping guideNewsletter-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-We have some great episodes coming with Claire Vo (CPO at LaunchDarkly, Founder at ChatPRD), April Dunford (Marketing Expert and Author, Obviously Awesome), and Eric Simons (CEO and Founder, Bolt).I’m so excited to share them with all of you. 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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Reforge Growth Crash Course in 82 Minutes | The Brian Balfour Episode
Feb 25, 202501:21:26Tap to summarizeBrian Balfour is the Godfather of Growth. He created the Growth Series at Reforge and was VP of Growth at Hubspot. In this episode, he shares a concise summary of Reforge's best growth ideas.-Brought to you by:GibsonAI: Your AI Database EngineerVanta: Automate compliance, manage risk, and prove trust-We're covering:Preview - 00:00:00Retention is the Core of Growth – 00:02:38Use Case Map to Define Retention Metric – 00:14:22Ways to Improve Retention – 00:17:18Retention as a Growth Strategy – 00:21:29Evaluating Monetization – 00:24:53Aligning the Value Metric with Monetization – 00:30:14Why Funnels Are Dead – 00:34:10AI Growth Loop – 00:37:06Why Traditional PDCs Are Becoming Obsolete – 00:47:41Collapse of the Prototype-Test-Learn Cycle – 00:52:43Prototyping for PMs – 00:58:25Measuring AI Products – 01:01:08Understanding Problems with AI Product Strategy – 01:06:06Overcoming Burnout and Coming Back Better – 01:15:56-Where to find Brian:LinkedInWebsiteReforge-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-We have some great episodes coming with Colin Matthews (AI Prototyping Expert), Claire Vo (CPO at LaunchDarkly, Founder at ChatPRD), and Jason Cohen (Founder of WPEngine).I’m so excited to share them with all of you. Get full access to Product Growth at www.news.aakashg.com/subscribe
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The Marty Cagan Episode: Product Management Crash Course in 61 Minutes
Feb 21, 202501:01:28Tap to summarizeMarty Cagan has shaped how the world thinks about product management.He is a master of product strategy, product discovery and product delivery.-Brought to you by:WorkOS: Your app, enterprise readyVanta: The best tool to automate compliance, manage risk, and prove trustGibsonAI:-We're covering:Preview - 00:00:00Principles Adopted by the Best Companies – 00:03:17Transformation Without Real Product Leaders – 00:12:56Managing Team Friction – 00:17:41Driving Transformation as a PM – 00:23:14How Product Leaders Can Transform Their Company – 00:37:38Coaching a Product Leader – 00:42:28What to Avoid When Hiring a Coach – 00:44:26Key Principles for a Strong Product Organization – 00:49:48Marty’s Favorite Product Culture – 00:54:32Marty’s Least Favorite Product Concept – 00:58:10-Where to find Marty:LinkedInWebsite-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-We also have some great episodes coming with Brian Balfour (Founder, Reforge; & Fmr VP Growth, Hubspot), Colin Matthews (AI Prototyping Expert), and Aakash Gupta.I’m so excited to share them with all of you. Get full access to Product Growth at www.news.aakashg.com/subscribe
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“Product Management isn’t going to exist in 5 years” - 2x CPO
Feb 18, 202501:40:06Tap to summarizeAbishek Viswanathan has led product teams at Apollo.io and QualtricsIn this episode, he shares everything it takes for a PM to stay relevant in this AI-driven era.-Brought to you by:Attio: The next generation CRMVanta: The best tool to automate compliance, manage risk, and prove trustMaven: I’ve just launched my unique curation of their top courses-We're covering:Preview - 00:00:00Designers in the AI-Driven Era – 00:09:19AI Tools for Rapid Prototyping – 00:17:44Why PMs Must Be Technical with AI – 00:30:13Product Engineers Taking on PM Roles – 00:40:50The Two Categories of Product Engineers – 00:45:33The Future of Product Management – 00:51:15How Technical PMs Impact a Company – 00:57:11How Companies Will Win by Embracing This Shift – 01:04:38The Rise of the Feature Factory Era – 01:08:13Why the Top Two Jobs of a PM Are the Same – 01:14:13The Expanding Role of Product Engineers Beyond Building – 01:20:23Lessons from Failures as a Product Builder – 01:27:19Balancing Work and Execution as a Product Leader – 01:34:55-Where to find Abishek:LinkedIn-Email productgrowthppp at gmail.com to discuss advertising or guest opportunities.-We have some great podcasts coming from Marty Cagan (The legend himself), Brian Balfour (Founder, Reforge; & Fmr VP Growth, Hubspot), and Colin Matthews (AI Prototyping Expert).I’m so excited to share them with all of you. Get full access to Product Growth at www.news.aakashg.com/subscribe
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