Powered by RND
PodcastsBusinessProduct Growth Podcast

Product Growth Podcast

Aakash Gupta
Product Growth Podcast
Latest episode

Available Episodes

5 of 93
  • Complete Course: AI Experimentation
    "AI has been the biggest driver of change in experimentation I've seen in my career."That's Frederic De Todaro, Chief Product Officer at Kameleoon (profitable SaaS with 2K+ customers).Fred has been at Kameleoon for 12+ years. In that role, he's helped thousands of teams use AI to experiment faster and smarter.In today’s episode he’s breaking down:How AI changes experimentationHow to experiment with AI featuresLast week, I covered how one aspect of this: vibe experimentation. Today’s video is the A to Z AI impact. If you experiment at work, this episode is for you.----Check out the conversation on Apple, Spotify and YouTube.* Mobbin: Discover real-world design inspiration* Jira Product Discovery: Build the right thing, reliably* AI Product Strategy Certificate for Leaders: Get $550 off----Timestamps:00:00 How AI Changed Experimentation Overview01:54 The 4 Steps of Experimentation Framework14:12 ADS16:00 How AI has Changed Experimentation21:08 User Behaviour Models26:56 Multi-Armed Bandit vs Contextual Bandit30:05 ADS31:55 AI Content Genration35:13 How Vibe Coding Changes Experimentation41:35 Live Demo From Idea to Running Experiment in 2 Minutes43:36 Two-Minute Build Achievement51:49 How to Measure AI Features Properly54:17 Measuring RAG Systems 3 Key Metrics01:07:18 Best Experimentation Company Booking.com01:10:10 Biggest PM Mistakes in Experimentation01:13:52 Ending----Key Takeaways1. Build is the bottleneck. Most teams can't A/B test because developers are busy. AI removes this constraint anyone can now create experiments in minutes using plain English.2. 80% of experiments fail. But with AI opportunity detection, you can drill into failed experiments to find hidden wins, like features that work great on mobile but fail on desktop.3. Vibe coding meets experimentation. It's not enough to build prototypes quickly. You need to test them with real users at scale. Prompt-based experimentation bridges this gap.4. Context is everything. AI performs best when it has access to your website's framework, design system, and past experiments. The more context, the better the ideas and implementations.5. Humans still matter. PMs bring business context, data scientists ensure statistical rigor, and AI handles the grunt work. It's augmentation, not replacement.6. Start simple with feature flags. You don't need to copy Booking.com overnight. Begin with feature flags, then rollouts, then full experimentation. AI makes each step easier.7. Measure beyond usage. For AI features, track: How many prompts to success? Time from idea to live? How often do developers step in? These reveal true value.8. Multi-armed bandits for speed, contextual for personalization. Use multi-armed when you need quick answers. Use contextual when personalizing for each user.9. Discovery and experimentation are partners. Discovery tells you what users say they want. Experimentation tells you what they actually do. You need both for the full picture.----Check out the conversation on Apple, Spotify and YouTube.----Related Podcasts:* How to Build Things Faster as a Product Team* Lessons from Super-Senior IC Experimentation PM* Amplitude CEO: Demo, Story, and How They Build 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
    --------  
    1:02:34
  • OpenAI Head of Product (Integrity) on the Future of AI Agents, PM, and AI threats
    Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Jira Product Discovery: Build the right thing, reliably* AI PM Certification: Get $550 with code AAKASH550C7* The AI Evals Course for PMs: Get $1050 off with code ag-product-growth* Maven: Get $100 off my curation of their top coursesToday's EpisodeToday’s guest is at the epicenter of AI - and he hasn’t done any podcasts before.In today’s in-person chat, I sit down with Jake Brill, the Head of Integrity Product at OpenAI. He breaks down:* The GPT-5 launch* How OpenAI builds product* What the PM role looks in the the future with AI* The future of building product and the need to build agents into your product* What it takes to break into OpenAIIf you've ever wondered what it takes to work at OpenAI or how to build AI products at scale, this episode is for you.Your Newsletter Subscriber Bonus:For subscribers, each episode I also write up a newsletter version of the podcast. Thank you for having me in your inbox.(By the way, we’ve launched our podcast clips channel as well and we’re going to post most valuable podcast moments on this channel, so don’t miss out: subscribe here.)1. Integrity’s Role in the GPT-5 LaunchMost PMs think about launching products in terms of features and marketing. But when you're serving hundreds of millions of users with breakthrough AI, the real challenge is infrastructure that can handle the surge without breaking.OpenAI’s integrity team played 3 roles in GPT-5’s launch.Pillar 1 - Identity SystemsIdentity systems must scale from normal traffic to potentially 10x volume overnight. The technical challenge involves load balancing, database scaling, and ensuring your signup flow doesn't crash when everyone hits "Create Account" simultaneously.Pillar 2 - Financial InfrastructureFinancial systems need bulletproof payment processing and fraud detection as conversions spike. This includes sophisticated fraud prevention - bad actors specifically target new model launches to exploit capabilities with stolen credit cards.Pillar 3 - Safety SystemsSafety systems require multiple defense layers: model training, input/output classifiers, and behavioral monitoring. Red teaming happens during model training, at production checkpoints, and continuously post-launch.What most PMs miss is that integrity isn't just defensive - it's an enabler of scale. Without rock-solid integrity infrastructure, even the most advanced AI models can't reach their intended audience.Do you need an integrity team? If you're building consumer AI products at scale, handling sensitive data, or processing payments, the answer is probably yes.2. How OpenAI Builds ProductOpenAI operates with a unique product philosophy that breaks traditional PM playbooks. While most companies start with user problems and build solutions, OpenAI often starts with breakthrough capabilities and figures out how to bring them to humanity.Let’s zoom in on 5 key takeways about how they build product: Takeaway 1 - The Research-First ApproachJake describes this inverted approach: "We've got the best researchers in the world building the most powerful AI capabilities in the world. And sometimes it's like, holy moly, we just had this big research breakthrough. How do we bring this capability to humanity?"This research-first methodology requires unprecedented collaboration between product and research teams from day one, not as an afterthought.Takeaway 2 - Planning That Embraces UncertaintyTheir planning process intentionally embraces uncertainty. Teams plan quarterly but assume only 60-70% completion rates."If you do anything more than that, it probably means you weren't being flexible enough to the needs of the business. If you do anything less than that, probably didn't do a great job forecasting."Plans are written in pencil, not pen, with lightweight documents and async reviews wherever possible.Takeaway 3 - Product Reviews Stay Startup-StyleProduct reviews maintain startup-style directness despite OpenAI's scale. "People come in, it doesn't matter what level you are, you can talk directly with leadership. You don't have to have a fancy slide deck."This creates trust through transparency and hiring excellence rather than process overhead.Takeaway 4 - Heavy Slack CultureOpenAI runs almost entirely on Slack. Jake estimates "conservatively like 90% of my written communication is in Slack." They've built AI agents directly into their Slack channels for Q&A and operational tasks.Takeaway 5 - Iterative Deployment PhilosophyThe company's belief in iterative deployment shapes how they handle uncertainty. Rather than trying to predict every possible misuse case, they identify non-negotiable risks to mitigate before launch, build monitoring systems for edge cases, and "very quickly respond and build sophisticated solutions" based on real-world usage patterns."Actually, at the end of the day, it's really helpful to follow OpenAI's approach of iterative deployment, because once you start rolling things out, you can actually see in the real world how people accidentally might misuse your products."3. What the PM Role Looks Like in the AI FutureThree major shifts define the future PM, Jake's perspective from the epicenter of AI development reveals:Shift 1 - From Specification Writer to Evaluation ArchitectThe PM role is fundamentally shifting from specification writer to AI evaluation architect. Jake's team increasingly asks PMs to write evals because "they have the clearest vision of how the product should work in their head."The evaluation writing skill becomes critical as AI products require objective measurement frameworks. This differs from traditional product metrics by focusing on capability assessment rather than just usage measurement.Shift 2 - AI Prototyping Replaces Lengthy SpecsAI prototyping specifically transforms how PMs communicate vision. Instead of lengthy written specifications, PMs can now build functional demonstrations. "Rather than just writing a proposal for how something works, just build a prototype of how something could work and you put that in people's hands."This shift from description to demonstration accelerates feedback cycles and reduces interpretation gaps between teams.Traditional PRDs still matter, but they're becoming AI-enhanced and less wordy. "I think they're gonna go hand in hand the prototypes and the PRDs. I do think PRDs will be less wordy because you won't have to spend as much time describing oh you click on this button and this thing happens you can just show people."Shift 3 - The Human Elements Become More ImportantBut the human elements intensify rather than diminish. Jake emphasizes that empathy remains the most critical PM skill: "Fundamentally, you are building products for people who are nothing like you. They may live in a different part of the world. They may be a different age, different gender."In five years, Jake predicts PMs will need to manage not just humans, but agents.4. The Future of Building Product and the Need to Build Agents Into Your ProductEvery PM needs to think about building AI agents into their products - otherwise they’re missing out on the future of product. Why Agents MatterJake frames this transition clearly: "For those first couple of years, it's really been what we call assistance. You asked a model a question, you give it a prompt and you get a response…But where we foresee this technology going is not just question and answer, but rather, here's a task. Can you please complete it for me?"This transition requires rethinking product architecture at a fundamental level. Most digital products today are synchronous - "I take an action and a response or something else happens immediately."Agent-first products embrace asynchronous complexity where "someone clicks button and something far more complex can happen behind the scenes and you don't have to sit there waiting for response."Real-World Agent ImplementationJake already demonstrates this shift in his daily work. He uses agents for recruiting ("here's sort of the properties. Ideally, they have X years of design experience... Please go help and source some candidates"), medical research, and market analysis.For PMs specifically, agents excel at competitive analysis, presentation creation, and prototyping - areas where the combination of research depth and creative output provides immediate value.The strategic imperative is clear: "If you're not thinking about how to build products that are agentic in their fundamental nature, you're probably A, not maximizing the power of this technology and B, you're probably building a product that's going to be obsolete in a shorter time horizon."The Infrastructure ChallengeThe challenge extends beyond individual products to ecosystem integration. As Jake notes, "there's not going to be just one company building agentic products" and "the failure state would be if there's not a standard language for all of them to talk together."Products need to consider how their agents will communicate with other agents, requiring standards like MCP (Model Context Protocol) for tool integration and future protocols for agent-to-agent communication.Companies building agent-first products must also prepare for agent reliability challenges. Jake discusses the emerging problem of deceptive behavior: "agents learning to cheat" requires multiple defense layers including alignment training, behavioral monitoring, and constant red teaming.The solution involves "model training, model level classifiers, actor level classifiers, production monitoring, and then just like constant red teaming."5. What It Takes to Break Into OpenAIWhen I asked my newsletter subscribers for their dream company, OpenAI was the overwhelming #1 dream company 600 first-place votes compared to 200 for second place.Jake's advice for getting into OpenAI?* Start Building with AI: You really need to have a facility with AI products and models. There's no excuse for not—it's so easy to use these products, to vibe code, to play around with APIs.* Get a Referral: When we post jobs publicly, a lot of people apply. It really helps if someone at the company has worked with you and can speak to your skill.* Show Relevant Experience: Make your AI experience and domain expertise explicitly clear on your resume and LinkedIn.* Broad Background Wins: The best candidates aren't just specialists. They have experience across different areas (fraud AND ads AND growth) giving them multiple perspectives on ambiguous problems.Jake's own story is proof: he spent 2 months preparing while on paternity leave, treating the interview process with the intensity it deserved because "it felt like what I'd been working towards my whole career."The full conversation covers Jake's journey from Facebook's first internal PM hire to surviving a traumatic brain injury to leading integrity at the world's most important AI company. Essential listening if you're building your career in AI products. Watch or listen now. Key TakeawaysWhere to find Jake* LinkedInRelated ContentPodcasts:* Complete Course: AI Product Management* 5 AI Agents Every PM Should Build* Full Roadmap: Become an AI PMNewsletters:* How to become an AI Product Manager* AI Agents: The Ultimate Guide for PMs* The AI PM's Playbook: How Top PMs Are 10x-ing Their ImpactP.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. 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
    --------  
    1:21:06
  • He built the top AI agent startup | Flo Crivello, Former PM, now CEO & Founder, Lindy AI
    If you’ve ever said “I just wish I had an assistant who knew exactly how I think”... Lindy is that assistant. These agents aren’t demos. They’re real, customizable workflows anyone can build. No code.Flo Crivello (founder of Lindy and ex-Cruise/YC) joined us to show how his personal AI stack runs his entire workday: From triaging emails, summarizing meetings, blocking spam, managing contacts, and even sourcing candidates.We’re not talking theory here. You’ll see what’s possible today (no prompting skills, no code), just real agents doing real work when you give them instructions in plain English Language.If you’ve ever wondered: “What can AI actually do for me right now?”This episode answers it - line by line, screen by screen.----Brought to you by:Mobbin: Discover real-world design inspirationJira Product Discovery: Build the right thingProduct Faculty: #1 AI PM Certification (Class Starts: 15 Sep, get $500 off)----Timestamps:AI Agents Can Replace Your Team - 00:00:00The Top 5 AI Agents Every Entrepreneur Needs - 00:03:13The Golden Framework: When to Build an Agent - 00:08:50Keeping AI Agents Safe Without Killing Innovation - 00:09:42From Doer to Orchestrator: The New Management Mindset - 00:11:08Lindy vs ChatGPT: Individual Tools vs Work Platforms - 00:13:23Managing Agent Performance, Permissions & Costs - 00:14:26AD: Mobbin - 00:15:56AD: Jira Product Discovery - 00:16:55Managing Context and Token Costs - 00:17:51Lindy vs Competitors and Zapier - 00:18:58Inside Lindy's 5x Growth in 6 Months - 00:20:38The Salesperson Managing 40 AI Employees - 00:21:45The Soham Scandal: Hiring the 5-Job Engineer - 00:23:20From PM to AI Visionary: The Founding Story - 00:28:24AD: Maven - 00:31:21AD: AI PM Certification - 00:32:08The Pivot Philosophy: Action Produces Information - 00:32:54Should Every PM Become an AI Founder? - 00:37:17Talk to Customers, Build Product: Skip Everything Else - 00:38:45The Valley of Death: Surviving the Hardest Pivot - 00:41:02The AI Agent Agency Gold Rush - 00:44:08Big Tech is Missing the AI Agent Revolution - 00:47:42The 10-Year Vision: Fully Autonomous Companies - 00:48:01----Key Takeaways:Takeaways:01. Most startups are stuck in execution mode, when they should be in vision mode. Instead of spending 80% of time shipping and 20% dreaming, it should be the reverse. The best early-stage companies obsess over the product like artists—not analysts. That’s how you create something magnetic from day one. Not with OKRs. With taste.2. AI agents aren’t just features, they’re teammates. The real unlock with agents is that they collaborate like coworkers. You don’t “use” them, you talk to them. You delegate. They respond. They improve. And suddenly you’re not just automating—you’re offloading real cognitive work.3. You don’t build AI, you build trust. That’s the actual job. Trust is earned slowly: confirmation prompts, human-in-the-loop controls, clear audit trails. Give users the steering wheel first… and gradually ease them into self-driving. That’s how agents move from novelty to necessity.4. The smaller the scope, the sharper the tool. Most teams overbuild. The smarter play is to shrink the surface area until there’s zero ambiguity. That’s when you get magic: crisp execution, no confusion, and fast iteration. Think razor blade, not Swiss Army knife.5. From systems thinking to obsessive craft. Coming from Uber taught how to reason through complex marketplaces. But what unlocked breakthrough product thinking was obsessing over the UX like an artist—not just designing for logic, but for love.6. The future of work is voice → delegation → done.You won’t click through dashboards or jump tabs. You’ll just say, “Handle my recruiting outreach,” and it’ll happen. Behind the scenes: agents coordinating tasks, tracking progress, personalizing copy. And all you did was ask.7. Write Like Your Career Depends on It, Because It Does. Clarity of thought = clarity of writing. He said the best PMs he’s worked with are excellent writers. Not because it looks good, but because it reflects structured thinking.8. Product Sense Is a Muscle. He builds product by imagining it from the user’s emotional POV. Not “What features should we ship?” but “What would delight the user in this moment?”9. You Can't Delegate Taste. No matter how senior you are, if you're not involved in the details of product quality, you’ll lose the magic. He reviews designs himself, edits copy, and obsesses over UX, because product taste is not outsourceable.10. Go Where Product Is Sacred. A PM’s growth is tied to the culture. He picked Uber because product rigor was high. At Lindy, he made product obsession part of the DNA. If your company doesn’t value product deeply, leave.----Check out the conversation on Apple, Spotify and YouTube.----Related Podcasts:We Built an AI Employee in 62 mins (Cursor, ChatGPT, Gibson, Crew AI)Bolt Tutorial from the CEOThis $20M AI Founder Is Challenging Elon and Sam Altman | Roy Lee, Cluely----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
    --------  
    53:10
  • Teresa Torres' Step-by-Step Guide to AI Product Discovery
    In today’s episode, we have one of the two voices I wanted most when I started this podcast: Teresa Torres. Alongside Marty Cagan, she was in my top guests to have.That’s because she has trained over 17,000 PMs in 100 countries.And in today’s episode, she’s breaking down one of the most important elements of PMing: discovery. She gives a masterclass on how to use the learnings from her smash hit book Continuous Discovery Habits for the AI age, covering both:1. How to do discovery for non-AI features with AI tools2. How to discovery for AI featuresIf you’ve ever wondered why your product ideas sometimes flop, even when the interviews and research looked promising… you’re about to find out why!----Brought to you by:Miro: The innovation workspaceJira Product Discovery: Build the right thingParlance Labs: Practical consulting that improves your AIProduct Faculty: #1 AI PM Certification (Class Starts: 15 Sep, get $500 off)----Timestamps:Teresa's Background - 0:00Story-Based Interviewing - 3:20Fake Discovery Signs - 4:08Assumption Testing - 4:39Continuous Discovery Framework - 5:35AI Changes Discovery - 8:01AI Synthesis Concerns - 9:21AI Prototyping Era - 12:45Ads - 15:45AI Prototyping Workflow - 17:32Common Interview Mistakes - 22:24Interview Synthesis - 24:26OST Updates - 28:53Discovery Theater - 30:52Ads - 32:15Real Product Management - 34:03AI Product Discovery - 35:29Context Engineering - 39:16Orchestration Explained - 42:03Error Analysis - 46:01Observability & Traces - 46:05Claude Code Demo - 49:15Business Numbers - 52:56----Key Takeaways:Takeaways:01. Stop Shipping Blind. Your AI product isn't truly valuable until you validate it. Go beyond just building; understand user needs deeply with personas, journey maps, and jobs-to-be-done.02. MOM Test = Your Secret Weapon. The "MOM Test" is about asking questions that even your most supportive friend can't lie about. Don't ask if users "would" use your AI. Ask about their past behaviors and real problems. This helps you define success metrics and avoid building a fancy toy nobody needs. 03. Evaluate Everything, Relentlessly. AI Evals are not just a technical task for engineers, but the most critical tool for Product Managers to build high-quality, trustworthy AI products. Use them to understand, refine, and continuously improve your AI.04. Passion Won't Land the Job. Proof Will. "I'm passionate"...great I guess, but recruiters want to see what you've done. Your portfolio is your direct line to showing you can actually do the job.05. Build Your AI Portfolio. Now. Don't wait for experience. Create product teardowns of AI tools, develop case studies, or launch small side projects. This is your living, breathing proof of thinking and skill.06. Forget the Resume. Add Value. The ultimate job hack? Identify a problem at a target company and propose a solution, or even build a prototype before you apply. This showcases initiative and concrete skills.07. You’re At Fault (Brutal, I Know). Nailing Prompt Engineering is a direct path to better AI outputs. If your AI misbehaves, it's often your fault for unclear instructions. Refine your prompts for smarter, more reliable AI.08. Generic Resumes In The Bin! Forget sending generic resumes into the void. There are three distinct approaches: just a resume, adding a portfolio and cover letter, or the ultimate "Value Add" where you solve a company's problem before applying. 09. AI Will Do Your Dishes (Metaphorically). While AI Agents promise incredible autonomy and action, remember they still need clear goals and defined tasks. So, while your AI PM dream is big, maybe don't expect it to clean your dishes (yet) – stick to email automation for now!10. Don't Trust LLMs Blindly. LLMs are powerful. But they need continuous human validation and evaluation frameworks. Automate grading where possible, but always, always, have a human in the loop for critical judgment.----Check out the conversation on Apple or Spotify and the demo on YouTube.----Related Podcasts:AI Product Discovery: Complete CourseHow to Do Product Discovery Right with Pawel HurynMarty Cagan on the 4 Key Risks and Importance of DiscoveryHow to Survey and Learn From Your Users with George Harter----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
    --------  
    56:05
  • Building in Public: The 7 AI Tools I'm Using in My $1M+/Yr Business
    I made $1M in the last 12 months — with zero full-time employees. In this podcast, I’ll share and show you (watch the YT version) the 7 AI workflows that helped me scale faster, save over $400K in costs, and launch multiple income streams, all powered by AI agents. You’ll see exactly how I use tools to: - Automate my inbox - Build and ship SaaS prototypes - Write and produce video ads - Grow a podcast to 50K+ listeners/episode - Repurpose and distribute content across platforms - Book high-profile guests - Run a content engine with zero human ops----Brought to you by:Miro: The innovation workspace is your team’s new canvasJira Product Discovery: Build the right thingMobbin: Discover real-world design inspirationParlance Labs: Practical consulting that improves your AI----Timestamps:Preview – 00:00:00AI Workflow 1 (Zapier) – 00:00:48AI Workflow 2 (v0) – 00:03:13AI Workflow 3 (Cursor) – 00:08:55AI Workflow 4 (v0.3) – 00:12:04AI Workflow 5 (Lindy) – 00:16:32AI Workflow 6 (Riverside) – 00:19:03AI Workflow 7 (Claude Copilot) – 00:22:47Summarizing Everything – 00:27:52----Check out the conversation on Apple, Spotify and YouTube.----Related Podcasts:This PM Built a Six-Figure ($100K+) AI Side HustleHe Built a $2M/Yr One-Person Business - Steal His PlaybookThis PM was Laid Off - Now he has 125K followersHer Layoff Went Viral - Now She has 300K+ SubscribersHow I make $18K/mo with a niche podcast (STEAL THIS)This Ex Amazon VP Makes $950K In Retirement----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
    --------  
    31:05

More Business podcasts

About 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
Podcast website

Listen to Product Growth Podcast, Lead on Purpose with James Laughlin and many other podcasts from around the world with the radio.net app

Get the free radio.net app

  • Stations and podcasts to bookmark
  • Stream via Wi-Fi or Bluetooth
  • Supports Carplay & Android Auto
  • Many other app features
Social
v7.23.3 | © 2007-2025 radio.de GmbH
Generated: 8/31/2025 - 2:10:20 AM