Product Growth Podcast

• The AI PM’s Guide to Building AI Agents, with Warp CEO Zach Lloyd

  Today’s EpisodeAs an AI PM, you’re probably tired of building AI Agents and don’t know how to monetize them.But what if I told you there’s a company adding $1 million ARR every 10 days with their AI agent?Zach Lloyd, CEO of Warp and former Google engineering leader, cracked the code. His terminal-based AI agent has 700,000+ active developers paying real money.This episode is his complete playbook for AI PMs who want to build agents that actually make money.I hope you enjoy this one!----Brought to you by:* Vanta: Automate compliance, manage risk, and prove trust* Kameleoon: Leading AI experimentation platform* Amplitude: The market-leader in product analytics* The AI Evals Course for PMs: Get $1155 off with code ‘ag-evals’----Timestamps00:00:00 - Intro00:01:55 - Interview Begins00:02:02 - Warp's Scale & Growth00:03:08 - The Turning Point00:04:32 - Learn or Get Left Behind00:05:50 - Framework for AI Value00:08:30 - Warp's Development Process00:12:28 - UX Challenges in Agentic Products00:14:53 - Ads00:19:29 - Who's Making Money with Agents00:28:31 - Future Predictions00:29:24 - Ads00:30:26 - Contrarian Takes on AI's Future00:35:44 - 90-Day Roadmap for PMs00:38:33 - Outro----Key Takeaways----Where to Find Zach Lloyd* Linkedin* X (Twitter)* Warp----Related ContentPodcasts:* He built the top AI agent startup* AI Agents for PMs in 69 Minutes* How to Build AI Agents (and Get Paid $750K+)Newsletters:* AI Agents: The Ultimate Guide for PMs* Ultimate Guide to AI Prototyping Tools* How to Land a $300K+ AI Product Manager Job----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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• The AI PM's Guide to Security - with Okta's VP of PM & AI, Jack Hirsch

  Today's EpisodeHere's what's happening right now:Someone can clone your voice from a few YouTube videos and call your help desk pretending to be you.AI can build a perfect fake of your login page in minutes.This isn't some distant future threat. Jack Hirsch, VP of Product at Okta, sees this happening every day. Okta protects millions of logins and Jack has a front-row seat to how AI is completely changing cyber attacks.And the scary part is most PMs have no idea this is happening to their products.That's why I brought Jack on the show. He breaks down what's really happening and what you need to know as someone building products in the AI era.----Brought to you by:* Amplitude: The market-leader in product analytics* The AI Evals Course for PMs: Get $1155 off with code ‘ag-evals’* The AI PM Certificate: The #1 AI PM certificate* Kameleoon: Leading AI experimentation platform----Key Takeaways1. Identity is Everything: Over 80% of breaches stem from identity attacks, not device or network vulnerabilities. You cannot get security right without getting identity right - this is the new reality.2. DPRK Infiltration Operations: North Korean agents are passing full interview processes, getting hired, having laptops shipped to device farms, and operating as inside threats within major organizations.3. AI Agents = Security Blindspot: Companies deploy AI agents en masse without treating them as identities requiring access management. JP Morgan's CISO called this out as the biggest current threat vector.4. Help Desk Social Engineering: Attackers use AI voice cloning and deepfakes to impersonate employees calling help desk for password resets, MFA bypasses, and account access - often successfully.5. Session Security Over Time: Authentication degrades after login. Okta focuses on continuous session monitoring and risk signal sharing between security vendors rather than constant MFA prompts.6. T-Shaped Identity Strategy: Deep identity security (phishing-resistant auth, lifecycle management, risk sharing) plus broad integration across all enterprise systems - not just SSO and MFA.7. Cross-App Access Standard: New OAuth standard allows AI agents to inherit user permissions across enterprise apps without individual OAuth dances for thousands of employees.8. Essential vs Discretionary AI: Essential AI (bot detection, fraud prevention) stays always-on. Discretionary AI (log summaries, access reviews) gives customers opt-out control for compliance.9. AI Product Principles: Accelerate don't abdicate, solve real problems before prototyping, ignore AI hype cycle. Use AI as thought partner, not replacement for product judgment and domain expertise.10. Personal Security Stack: Lock credit reports immediately, use password manager with unique passwords, enable passkeys everywhere, lock phone number with carrier PIN to prevent SIM swapping attacks.----Related ContentPodcasts:How to Get a Product Leadership JobHow He Became a Series C VP of Product in 10 Years“Product Management isn’t going to exist in 5 years” - 2x CPONewsletters:The Product Leadership Job SearchThe Product Leader’s Ultimate Guide to Process ChangesProduct Leadership Interviews (GPM, Director, VP): How to Succeed----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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• How to Build AI Agents to 10x your PM Productivity with CEO of Relay.app (fmr Dir PM of Gmail)

  You use ChatGPT. But being an AI-powered PM means also using AI agents.In my slack poll, only 2% of you said you use AI agents for productivity. So I want to break that down and make it dead clear: 1) why you should use AI agents and 2) how you should build them.So in today’s episode, I’ve brought in Jacob Bank, former Director of PM at Google (Gmail, Calendar) and now CEO of the AI agent builder company Relay.app.He shares all his secrets - his 12 agent EA, his 40 agent marketing team, and his agent to synthesize agent updates. I hope you enjoy.----🏆 Thanks to our sponsors:Miro: The innovation workspace is your team's new canvasJira Product Discovery: Plan with purpose, ship with confidenceMobbin: Discover real-world design inspirationProduct Faculty: Product Strategy Certificate for Leaders (Get $550 off)----⏰ Timestamps:00:00 Intro01:49 Meet Jacob: The AI Agent Pioneer02:18 Managing Agent Notification Overload04:13 Current AI Agent Limitations Explained06:59 Relay's Growth & Bootstrap Strategy10:25 The Bull Case for AI Agent Market15:14 Ads17:18 Who's Adopting AI Agents Fastest20:46 Top 10 AI Agent Use Cases for PMs22:48 Choosing the Right Agent Platform28:44 Jacob's 55-Agent Marketing Team Breakdown31:47 Ads34:45 Building AI Agents Into Your Product38:10 MCP Protocol & Future of APIs41:43 Why Jacob Left Google Director Role44:25 Brutal Truth: PM-to-Founder Reality Check48:52 Outro----Key Takeaways1. Real agents need five components working togetherIntelligence (LLM), Knowledge (proprietary data), Memory (interaction history), Tools (APIs that change world state), Guardrails (validation and safety). Most "agents" are just LLM wrappers missing the other four components.2. No-code tools compress development cycles 100xLangflow + v0 enable 30-minute prototype-to-production workflows. Build competitive analysis agents live on screen. The cost barrier disappeared while customers still can't articulate what they want until they see it working.3. Cart-before-horse development beats traditional PM processSkip months of research. Build working prototypes first, test with real users, iterate based on feedback, then write focused PRDs. Speed beats perfection when technology moves this fast.4. FAANG salaries reflect desperate demandLevel 6-7: $750K+ total compensation. Level 8+: $1.2-1.5M total compensation. OpenAI: $900K+ for comparable roles. Growth rate: 2-3x faster than traditional PM positions because supply can't meet demand.5. The proven 18-month roadmap works systematicallyMonths 1-3: master fundamentals, build working agent solving personal problems. Months 4-9: scale to 10-20 real users, learn evaluation systems. Months 10-18: contribute to open source, prove you outperform existing team members.6. Vibe coding interviews test product judgment, not technical skillsDemonstrate structured thinking through prompt engineering, incorporate user insights in second iterations, show measurement frameworks in third iterations. They're evaluating product sense through AI interactions.7. Target problems with three characteristics for defensibilityDomain expertise you already possess, unstructured data requirements, complex decision-making processes. This combination creates competitive moats that simple AI features cannot replicate easily.8. Evaluation frameworks must come before codingMeasure usage adoption, outcome achievement, and user experience satisfaction. Include speed metrics (prompts to completion) and accuracy benchmarks (goal success rates) to validate that AI actually democratizes building.9. Company cultures reward different AI approachesMicrosoft: innovation without business constraints. Amazon: profit-focused execution speed. Meta: collaboration with world-class engineering talent. Google: user experience perfection with iteration time.10. Essential PM tools everyone needsCustomer interaction analyzer across all channels, AB testing simulator using AI personas at scale, document reviewer trained on your manager's specific feedback patterns an----Related ContentRelated Podcasts:* He built the top AI agent startup* AI Agents for PMs in 69 Minutes* How to Build AI Agents (and Get Paid $750K+)Realated Newsletters:* AI Agents: The Ultimate Guide for PMs* Ultimate Guide to AI Prototyping Tools* How to Land a $300K+ AI Product Manager Job----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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• FAANG PM Reveals How to Build AI Agents (and Get Paid $750K+)

  AI agent PM roles are the fastest-growing, highest-paid positions in tech. These jobs pay $750K+ (TC in SF/NY) and are growing 2-3x faster than traditional PM roles.But most people don't know how to actually build AI agents. They think it's just ChatGPT with a fancy interface.Today I sat down with Mahesh Yadav, who's worked as a PM at Meta, Amazon, Microsoft, and Google. He's built AI agents at scale for 8+ years and now teaches hundreds of PMs at top companies.He breaks down the exact playbook: how to build agents, the 18-month roadmap to $750K+ roles, and what FAANG companies look for in vibe coding interviews.If you want to learn to build AI agents, this is your blueprint.Check out the conversation on Apple, Spotify and YouTube.----Brought to you by:* Maven: Get $100 off my curation of their top courses with code ‘AAKASH550C7’* Miro: The innovation workspace is your team’s new canvas* Kameleoon: Leading AI experimentation platform* The AI Evals Course for PMs & Engineers: Get $1155 off with code ‘ag-evals’* Amplitude: The market-leader in product analytics----Timestamps00:00 - Introduction & Overview01:40 - What Makes an AI Agent PM02:37 - Building the Backend Agent16:32 - Creating the Frontend with V025:27 - What Defines an AI Agent vs AI Product30:15 - AI PM Interview Requirements34:08 - Cart Before the Horse Development37:15 - Breaking into FAANG: Mahesh's Story42:17 - Internal Transfer Strategy50:40 - Comparing Microsoft vs Amazon vs Meta vs Google54:28 - AI Agent PM Job Market & Salary Data57:26 - Can Anyone Become an AI PM?59:14 - 18-Month Roadmap to AI PM1:05:01 - AI Agents for Regular PMs1:08:47 - Business of Mahesh & Course Success----10 Steps to a $750K+ AI Agents Job:1. Build First (Not Study)The biggest mistake aspiring AI PMs make is spending months reading about AI instead of building. Companies like Google aren't looking for people who know frameworks—they want builders who have actually shipped AI products. Start with tools like Langflow for no-code backends and V0 for frontends.2. Master AI FundamentalsYou need to know how models work, how data contributes to these models, and how to evaluate agent performance. Can you make smart choices between different models? Do you understand how these models are built and how to interact with them? This knowledge separates real AI PMs from pretenders.3. Show Scale ExperienceFAANG companies desperately need people who have seen one major technology transition and navigated it successfully. Whether it was cloud migration, mobile, or something else, show you can handle the chaos that comes with emerging tech. They're looking for people who experiment constantly because AI is new for everyone.4. Prototype in WeeksThe cost of prototyping has dropped 100x in two years. Instead of spending six months on research and PRDs, build a working prototype in 2-3 weeks and show it to customers. This "cart before the horse" approach is now the competitive advantage in AI product development.5. Get 10-20 Real UsersFind a real problem you can solve—ideally one where you have PhD-level expertise, involves unstructured data, and requires complex decision-making. Build an agent to solve it and get at least 10-20 people actually using it. This teaches you evaluation and iteration in ways no course can.6. Scale to ProductionHire a small team of engineers (even remotely) and get your prototype into real production with 100+ users. This teaches you the difference between a demo and a scalable system. Many startups will let you do this for free in exchange for the experience and expertise you bring.7. Target Dream CompaniesPick your top 10 target companies and start contributing to their open communities. Run evaluations on their products for free. Show them gaps in their AI capabilities. Build features for their open-source models. Make yourself impossible to ignore by doing the work their PMs should be doing.8. Master Vibe CodingIn vibe coding interviews, they're not testing your technical skills—they're judging your product thinking. Show structured prompts, demonstrate how you iterate based on user feedback, and prove you can evaluate and improve AI systems. Practice the three-step framework: task, requirements, resources.9. Negotiate Multiple OffersAI PM roles at FAANG companies pay $750K-$1.5M+ total comp because demand far exceeds supply. Don't settle for one offer. The best candidates often get rejected by one company only to get double the salary elsewhere. Persistence pays—literally.10. Execute 18-Month TimelineMonth 1-3: Learn fundamentals and build your first agent. Month 4-6: Get 10-20 real users on a product you built. Month 7-12: Scale to production with 100+ users. Month 13-18: Contribute to target companies and interview. This timeline works because there's a level playing field in AI—your background matters less than your ability to ship.----Related Podcasts:* AI Agents for PMs in 69 Minutes* Full Roadmap: Become an AI PM* 5 AI Agents Every PM Should Build----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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• How to Build AI products in FinTech | $100B Lessons from Robinhood VP PM

  Today's EpisodeRobinhood just crossed $100 billion in market cap. Its stock has 5.5x'd in the past year. It's one of the hottest companies in fintech.But here's what most people don't understand: building products at Robinhood isn't just about moving fast and breaking things. It's about moving fast while navigating regulations that could shut you down.Today I sat down with Abhishek Fatipurya, VP of Product at Robinhood, who's been there for 9 years - from intern to VP. He walked me through how they built products that democratized finance while staying compliant.If you're building in fintech or any regulated industry, this is your playbook.----⏰ Timestamps:00:00 Intro01:34 Robinhood's AI Assistant: Cortex08:01 Advice for Products in Fintech12:10 IPO Stories14:37 Ads16:31 How To Build Innovative Products21:30 Why Most Fintech PMs Fail at Experimentation27:15 Ads28:54 Training the Team30:48 Abhiskek Journey at Robinhood39:40 Layoffs47:02 Robinhood's Scaling Journey (2016-2025)52:54 Should Prototypes Replace PRD's1:05:40 Why most Fintech PMs are Failing1:10:48 How To Build a Real Product1:18:08 Outro----Brought to you by:1. Kameleoon: Leading AI experimentation platform - kameleoon.com/prompt2. Mobbin: Discover real-world design inspiration - https://mobbin.com/?via=aakash3. AI Evals Course for PMs & Engineers: Get $1155 off with code ag-evals - https://maven.com/parlance-labs/evals?promoCode=ag-evlas4. Amplitude: The market-leader in product analytics - https://amplitude.com/session-replay?utm_campaign=session-replay-launch-2025&utm_source=linkedin&utm_medium=organic-social&utm_content=productgrowthpodcast----Key Takeaways1. Build AI products around problems customers already have rather than creating AI for AI's sake - Robinhood identified core pain points like "why did this stock move?" then built solutions that fit existing workflows instead of forcing new behaviors.2. Write your product's "swipeys" (onboarding screens) before building anything to force clarity on value proposition. If you can't convince a customer to hit "get started" in one sentence on mobile, you don't have a great product.3. Curate upstream data sources and focus on information rather than recommendations when building AI for regulated industries. Robinhood secures licenses with news providers while carefully prompting AI to avoid investment recommendations that trigger regulatory issues.4. Transform legal teams into product partners by hiring domain experts who get excited about building great customer experiences within regulatory constraints. Former SEC regulators who understand both rules and product vision push for better solutions rather than adding friction.5. Obsess over pixel-perfect details because great design shouldn't be reserved for high-net-worth customers in financial services. When the CEO spends time on animation details, it creates a competitive moat where most companies use bad design as barriers.6. Test everything relentlessly instead of copying surface tactics - Robinhood's referral program went through 60+ iterations, evolving from $10 cash to variable stocks. Most fintechs copy "$20 for $20" without understanding the deeper insight: give users your core service, not generic rewards.7. Democratize access by speaking to customer pain points rather than industry jargon. "Get in at the IPO price" addressed frustration of watching stocks gap up from $20 to $50 on opening day, making access emotionally resonant.8. Unite cross-functional teams under shared business goals by switching from functional silos to business unit GMs. This eliminates "death by a thousand departments" where each function adds friction without considering holistic customer experience.9. Think mobile-first to force clearer communication and simpler flows since mobile constraints eliminate unnecessary complexity. Even internal planning revolves around what features will be showcased in mobile-centric product keynotes.10. Ship meaningful features consistently to create a virtuous cycle where teams stay focused and the market recognizes you as an innovation engine. This product velocity compounds into sustained performance by demonstrating consistent execution capability.----Related ContentPodcasts:AI Product Leadership with Julie ZhuoAI Experimentation with Fred de TodaroAI Product Discovery with Teresa TorresNewsletters:Should you invest in your referrals channel?How to Build AI Products RightThe Fintech Super App Wars----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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