The Growth Podcast

Today’s EpisodeMost PMs are drowning in tools.You log into JIRA. Then Figma. Then Confluence. Then Notion. Then Google Analytics. Then Slack.Twenty different tabs. Twenty different logins. Zero flow state.Mike Bal runs product at David’s Bridal, a company undergoing massive digital transformation.And he operates from a single interface.Cursor and Claude Desktop sit at the center. Everything else connects through MCP and custom integrations.Research? Manus feeds into Claude. Analytics? Clarity exports into Cursor. Design? Figma pulls directly into his projects.This isn’t a tool stack. It’s an operating system.Today, Mike shows you exactly how to build it.----If you want access to my AI tool stack - Dovetail, Arize, Linear, Descript, Reforge Build, DeepSky, Relay.app, Magic Patterns, Speechify, and Mobbin - 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 9 seats left.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by Linear: Plan and build products like the best.----Key Takeaways:1. Operating systems beat tool stacks - Stop logging into 20 different UIs. Build one central interface through Cursor and Claude Desktop that connects to everything. The composable mindset adapts to your needs.2. MCP changes PM workflows forever - Model Context Protocol lets you connect JIRA, Figma, GitHub, Notion, Confluence through natural language. Check ticket status without opening JIRA. Compare designs without manual cross-reference.3. Design validation takes 30 seconds now - "Find my Confluence doc about Feature X, load this Figma design, compare them and tell me what I missed." Used to take 1-2 hours of manual comparison work.4. Manus dominates heavy research - Gives you multiple file outputs: sample CSVs, combined datasets, data sources report, quick start guide, markdown summary. All traceable back to sources. ChatGPT just gives responses.5. Research must stay external until vetted - The "conspiracy theorist LLM" problem is real. If you automatically feed everything into your system, AI anchors to wrong information. Vet research separately, then bring validated context in.6. PMs can build what required engineers - Mike built a colorization app for e-commerce in one morning. Migrated content to Sanity CMS in a few hours. All from natural language prompts in Cursor.7. Context switching kills productivity - Every time you open a new tab, you lose flow state. The operating system keeps you in one interface. The AI handles the context switching for you.8. Corporate IT restrictions become irrelevant - You already have Cursor or Claude Desktop. You already use JIRA, Figma, GitHub. Connect them through a better interface. No new tool approvals needed.9. Analytics workflows save massive time - Export Clarity data, upload to Cursor, prompt "analyze drop-offs and create visualizations." Takes 10 minutes vs hours of manual Excel work.10. AI native PMs think in prompts - "What do I need to do? What are the steps? What tools will help?" Treat AI as an extension of yourself, not a separate tool to learn.----Where to Find Mike* LinkedIn* Youtube* Website----Related ContentNewsletters:* AI Product Strategy* How to Build AI Products* AI Agents for PMs* Product Requirements DocumentsPodcasts:* AI Prototyping for PMs* How to Become an AI PM* Everything You Need to Know About AIPS. Please subscribe on YouTube and follow on Apple & Spotify. It helps! 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

Today’s EpisodeChatGPT just made huge waves with its Atlas browser. Perplexity made waves before that with its Comet browser. And Atlassian just spent a billion dollars to buy Dia.Big companies are making big moves in the AI browser space.But should you use an AI browser? Is it safe? Will it make you more effective as a PM?I asked this question at Berkeley last month during my keynote. Out of 500 PMs in the room, literally two hands went up.That needs to change.Naman Pandey has tested these browsers more extensively than anyone else. He runs the Ready Set Do podcast and has spent hundreds of hours finding the real use cases that actually work.Today, we’re putting all three browsers head-to-head. Same prompts. Same tasks. Live demos.You’ll see which browser wins for each use case, where they fall over, and the exact workflows to use them as a PM.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Jira Product Discovery: Plan with purpose, ship with confidence* Mobbin: Discover real-world design inspiration* Pendo: The #1 Software Experience Management Platform* Product Faculty: Get $550 off the AI PM Certification with code AAKASH550C7* Land PM job: 12-week experience to master getting a PM job----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 14 seats left.----Key Takeaways:1. AI agent browsers are underhyped for PMs - Only 2 out of 500 PMs at Berkeley were using them. If you're doing web research, competitor analysis, or data scraping, you're leaving hours on the table every week.2. The three browsers serve different purposes - ChatGPT Atlas for deep research across multiple pages. Perplexity Comet for real-time quick lookups. Arc Dia for workflow automation. They're not competing head-to-head.3. Atlas dominates data extraction - Scrape YC companies, find recruiters on LinkedIn, build competitor comparison tables. What took 2-3 hours now takes 10 minutes with one prompt.4. Comet wins on speed for real-time info - Stock prices, sports scores, breaking news. It's the fastest by far. Perfect for quick research sprints across Reddit, Twitter, and news sites.5. Dia automates repeated workflows - Monitor competitor pricing weekly. Document onboarding flows. Generate recurring reports. Set it once, let it run on schedule.6. Tab context is the hidden superpower - Open 5 competitor sites. Ask "What's the common pricing strategy?" The AI reads all tabs and synthesizes insights. Eliminates copy-paste friction.7. The job seeker use case is mind-blowing - "Find 20 PMs at Google, get their LinkedIn profiles, draft personalized DMs." Atlas does this in 15 minutes. Used to take 2-3 hours manually.8. Onboarding analysis becomes trivial - "Go through Notion's signup flow, capture screenshots, document each step." Dia does this in 5-10 minutes. Perfect for competitive analysis.9. Don't log into sensitive accounts - Banking, email, social media with private data - keep these in your regular browser. Use AI browsers only for public research and data extraction.10. The slowness matters less than you think - Yes, they're slow compared to Google. But if the alternative is 2 hours of manual work, waiting 10 minutes is a massive win. Batch requests and walk away.----Related ContentNewsletters:* AI Product Strategy* How to Build AI Products* AI Prototyping Tutorial* How to Become an AI PM* Ultimate Guide to OnboardingPodcasts:* How to Build ChatGPT Apps* AI Prototyping for PMs* Everything You Need to Know About AI* AI Product Management Course----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!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

This is a free preview of a paid episode. To hear more, visit www.news.aakashg.comToday’s EpisodeWhen you first start using AI prototyping tools, you get wowed.You type “create me a CRM application” and boom a fully functioning app appears in 60 seconds.But here’s the problem.It looks generic. The styling is basic. The features are vanilla. You’d never ship this to customers.This is AI slop.Sachin Rekhi was the former Head of Product at LinkedIn Sales Navigator. He’s now teaching thousands of PMs at Reforge how to master AI prototyping.----Brought to you by - Reforge:Get 1 month free of Reforge Build (the AI prototyping tool built for PMs) with code BUILD----Key Takeaways:1. Product shaping changes everything - Anthropic builds multiple prototypes for every problem, launches internally, sees what people use, then productionizes winners. This used to only be possible at Apple with massive labs.2. AI slop is real - Type "create a CRM" and you get generic styling, vanilla features, basic scenarios. Looks magical but you'd never ship it. The challenge is going from slop to production-grade prototypes.3. The 15-skill mastery ladder - Apprentice level: prompting, editing, design consistency. Journeyman: versioning, debugging, diverging. Master: functional prototyping, product shaping, analytics integration.4. Design consistency starts with baselining - Take screenshot of your product. Recreate it. Iterate until perfect. Save as template. Now every prototype inherits your design system automatically.5. Diverging is the secret weapon - Generate 4 design variants instead of 1. Magic Patterns has this built in. Or use multiple tools to get 8 options. Evaluate alternatives like designers do.6. Functional prototypes unlock real validation - Integrate OpenAI API for actual responses. Add PostHog for session recordings and heatmaps. Build surveys. Track clicks. Test with real data, not mockups.7. The tools face-off: which to actually use - Bolt for speed. V0 for beautiful UIs. Replit for full-stack. Magic Patterns for product teams with diverging. Reforge Build for context integration. Cursor for technical PMs.8. The $5/month unlimited execution hack - Host n8n on Hostinger instead of paying per execution. Get unlimited runs. Build workflow that backs up to Google Drive for version history.9. PMs can build what used to require engineering - Calendar integration. Email agents. Analytics dashboards. Multi-model comparison. Survey collection. All from prompts. No code required.10. Traditional workflows beat agents for production - Workflows save tokens, run faster, and are more reliable. Use agents only when tasks need real decision-making. For known processes, use workflows.----Where to Find Sachin* LinkedIn* Newseltter* X* Youtube* Reforge cources----Related ContentNewsletters:* AI Product Strategy* How to Build AI Products* AI Prototype to Production* AI Prototyping Tutorial* Product Requirements DocumentsPodcasts:* 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.

This 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.

Today’s EpisodeEveryone’s demoing AI features. Few are shipping them to production reliably.The gap? Evals.Not the theoretical kind. The real-world kind that catches bugs before users do.Hamel Husain and Shreya Shankar train people at OpenAI, Anthropic, Google, and Meta on how to build AI products that actually work. Their Maven course is the top-grossing course on the platform.Today, they’re walking you through their complete eval process.----Brought to you by:* The AI Evals Course for PMs & Engineers: You get $800 with this link* Vanta: Automate compliance, Get $1,000 with my link* Jira Product Discovery: Plan with purpose, ship with confidence* Land PM job: 12-week experience to master getting a PM job* Pendo: the #1 Software Experience Management Platform----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. AI evals are the #1 most important new skill for PMs in 2025 - Even Claude Code teams do evals upstream. For custom applications, systematic evaluation is non-negotiable. Dog fooding alone isn't enough at scale.2. Error analysis is the secret weapon most teams skip - Looking at 100 traces teaches you more than any generic metric. Hamel: "If you try to use helpfulness scores, the LLM won't catch the real product issues."3. Use observability tools but don't depend on them completely - Brain Trust, LangSmith, Arise all work. But Shreya and Hamel teach students to vibe code their own trace viewers. Sometimes CSV files are enough to start.4. Never use agreement as your eval metric - It's a trap. A judge that always says "pass" can have 90% accuracy if failures are rare. Use TPR (true positive rate) and TNR (true negative rate) instead.5. Open coding then axial coding reveals patterns - Write notes on 100 traces without root cause analysis. Then categorize into 5-6 actionable themes. Use LLMs to help but refine manually.6. Product managers must do the error analysis themselves - Don't outsource to developers. Engineers lack domain context. Hamel: "It's almost a tragedy to separate the prompt from the product manager because it's English."7. Real traces reveal what demos hide - Chat GPT said the assistant was correct but missed: wrong bathroom configuration, markdown in SMS, double-booked tours, ignored handoff requests.8. Binary scores beat 1-5 scales for LLM judges - Easier to validate alignment. Business decisions are binary anyway. LLMs struggle with nuanced numerical scoring.9. Code-based evals for formatting, LLM judges for subjective calls - Markdown in text messages? Write a simple assertion. Human handoff quality? Need an LLM judge with proper rubric.10. Start with traces even before launch - Dog food your own app. Recruit friends as beta testers. Generate synthetic inputs only as last resort. Error analysis works best with real user behavior.----Where To Find Them* LinkedIn:* Hamel: Hamel’s LinkedIn* Shreya: Shreya’s LinkedIn* AI Evals Course: World’s best AI Evals Course (You get $800 off with this link)Related ContentNewsletters:* AI Evals* AI PM Observability* AI Testing* LLM Judge* AI Prototype to Production* AI Product Strategy* How to Build AI Products* Prompt EngineeringPodcasts:* AI Evals: Everything You Need to Know to Start* Everything you need to know about AI (for PMs and builders)* Carl Vellotti on Claude Code* Marily Nika on Google AI PM Tool Stack* Pawel Huryn on n8n for PMsPS. Please subscribe on YouTube and follow on Apple & Spotify. It helps! 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

Today's EpisodeCarl Vellotti is back.His first episode hit 30k views. My most popular episode in months.Today, he’s giving you the advanced playbook for Claude Code.Claude Code hit $1 billion ARR in December. Fastest product ever to reach that milestone. Under 6 months.Carl has been building with Claude Code every single day. He’s made all the mistakes. He’s learned all the expert workflows and tips.In today’s episode, he shares everything.----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.----Brought to you by:Amplitude: The market-leader in product analyticsPendo: the #1 Software Experience Management PlatformJira Product Discovery: Move discovery and roadmapping out of spreadsheetsMiro: The innovation workspace----Key Takeaways1. Claude Code hit $1B ARR in 6 months - fastest product ever. Anthropic optimized for power users doing deep work. Fewer users, insanely deep usage. Carl: "I spend all day in Claude Code. It gets to the point where you never really have to leave."2. MCPs connect Claude to everything in 2 minutes - Model Context Protocol invented by Anthropic. One command to install Linear, Google Workspace, Slack. Essential stack: documents first, task management second, communication third, data sources fourth.3. End-to-end PM workflow takes one morning instead of one week - Survey creation → analysis → PRD → presentation → 19 tickets. All through MCPs. Carl didn't use templates. Opus 4.5 handled everything.4. Skills are pre-built templates but don't always auto-trigger yet - Solution: specify explicitly. "Create presentation using your presentation skill." Build Skills for anything you do more than twice. That's the compound effect.5. Real Google Slides, not images - Carl's presentation skill created 19 fully editable slides from PRD. Takes a few minutes because Claude creates slides in parallel. "This is saving you hours. We used to spend entire afternoons turning PRDs into decks."6. GitHub turns Claude into remote worker - Create issues from your phone. @mention Claude. It works while you're away. Carl's journal is a private GitHub repo. Voice transcriptions → issues → Claude updates markdown.7. Workflows beat agents for production - Level 1 workflow: 5,000 tokens, 40 seconds. Level 3 agent: 90,000 tokens, 90 seconds. Carl's rule: "If something can be expressed as code, code it. Leave agents for cognitive work."8. Production best practices separate hobbyists from pros - Set error workflows. Add retry logic (3 attempts, 1-second delays). Pin data during development. Use reasoning effort appropriately. Write detailed tool descriptions.9. Real challenge is building reusable workflows - Learning basics takes a day. First workflow takes hours. But having 50 workflows built over months means everything is automated. Carl: "Because I have workflows for all these things already built, I can do it all in one shot."10. Tools improve faster than you can learn them - Carl: "By the time you see this, there might be Claude 5." Your workflows from today will 10x when better models drop. PMs who started 6 months ago aren't just 6 months ahead, they're 100x ahead because systems compound with every improvement.----Where to Find Carl Vellotti* Linkedin* X (Twitter)* Instagram* NewsletterRelated ContentNewsletters:* How to Use Claude Code Like a Pro* Steal 6 of My Claude Skills* Claude Skills Tutorial* AI Agents: The Ultimate Guide for PMs* Practical AI AgentsPodcasts:* The Ultimate Guide to n8n for PMs, with Pawel Huryn* This is what a Google AI PM’s Tool Stack Looks Like, with Marily Nika* How to Use Claude Code Like a Pro (Carl’s First Episode)----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!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

Marily Nika and I filmed my 7th most popular episode a year ago.She broke down everything on how to become an AIPM because she’s done it. She is an AIPM at Google with 11 years of experience.Today, she’s back with a completely new episode. She’s dropping every AI tool she uses daily as an AIPM.Not theory. Not hype. The actual 6 tools she uses multiple times every single day.Today she’s dropping all the expert tips and tricks. She’s made the mistakes so you don’t have to.----Today’s guide covers:* The AI PM Tool Stack* Google AI Studio for Prototyping* Opal for Mini Apps* Notebook LM for Domain Expertise* Perplexity for Reddit Research* ChatGPT for Your Voice* Fireflies and Getting Tools at Work* The 18-Month AIPM Roadmap* The AIPM Interview Red Flags----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Jira Product Discovery: Move discovery and roadmapping out of spreadsheets* Vanta: Automate compliance across 35+ frameworks* Maven: Improve your PM skills with awesome courses. Discount with my link* Mobbin: Discover real-world design inspiration* Product Faculty: Get $500 off the AI PM Certification with code AAKASH25----Key Takeaways1. Marily's stack is just 6 tools - Google AI Studio for prototyping, Opal for mini apps, Notebook LM for learning, Perplexity for user research, ChatGPT for PRDs, and Fireflies for meetings. Each maps to one PM workflow. No tool hopping.2. Prototype before writing PRDs. Marily builds a working app in AI Studio first, then brings engineers in to debate the actual thing. Saves weeks of back-and-forth on documents. PRDs are now for complex cross-functional work only.3. Notebook LM learned a 4-hour video in 15 minutes. Marily had an interview the next day. She uploaded the job description and a 4-hour investor relations video. It gave her 15 key points. She memorized them and crushed the interview.4. Perplexity's Reddit filter is your secret weapon. Turn off web search, turn on discussions and opinions. Ask "would young professionals be interested in a fitness ring?" Get 20+ Reddit sources instantly. Know what users actually want.5. Marily's PRD generator has 10,000+ users. She trained a ChatGPT custom GPT with her voice and old PRDs. It asks probing questions before generating. Gets PRDs done in days instead of weeks. She's not embarrassed to use AI at work.6. Tool selection has 4 rules. Does it save 10x time (not 2x)? Does it work across contexts? Does it work with your company's limitations? Does it compound over time? If not all 4, delete it.7. "Be like a crab" for AIPM roles. Move adjacent to your experience. Hearing aids → AirPods PM. ESPN journalism → Meta sports AI PM. Don't ignore your past experience. It's your competitive advantage.8. Red flag in AIPM interviews - missing PM craft. Ex-ML scientists dive into algorithms without asking why, who, and how to measure success. AI changes HOW you fulfill use cases, not the use cases themselves.9. Who replaces PMs? Not AI. PMs who use AI when you're not. Don't be embarrassed about using AI at work. It's not cheating. The gap is widening between PMs who use these tools and those who don't.10. Every PM will become an AIPM by 2026. Show Marily any product and she'll find the AI use case. Even retail stores use cameras and AI to monitor which areas get traffic. The AIPM title will just become PM.----Where to Find Marily* LinkedIn* Twitter* Website* YouTube* Newsletter* Maven - Her course is part of my special curation with Maven----Related ContentNewsletters* AI Foundations for PMs* How to Become an AIPM* AI Prototyping for PMs* AI PRDs* The Complete AI PM Course* AI Product Strategy* ChatGPT for PMsPodcasts* Pawel Huryn on n8n* Alex Danilowicz on AI Prototyping* Hamza Farooq on Landing AIPM Jobs* Todd Olson on Upskilling to AIPM* Rachel Wolan on AI Product Leadership----If you want access to AI tools for free, get Aakash’s bundle and access to 9 AI products for an entire year.Are you searching for a PM job? Join me + 29 others for an intensive 12-week experience to master getting a PM job.----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!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

This is a free preview of a paid episode. To hear more, visit www.news.aakashg.comPawel Huryn is the guest behind my most popular episode ever (52K+ views).Today, he’s back to give you a masterclass in one of the most exciting AI tools out there: n8n.n8n is the most powerful workflow automation tool that combines two things: traditional workflow automation and building AI agents.And Pawel has been knee-deep in n8n more than almost anyone else in the world.He’s tried everything. He’s made all the mistakes. He’s learned all the expert workflows and tips and tricks.In today’s episode, he walks through building real n8n workflows from scratch.-----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Amplitude: The market-leader in product analytics* Vanta: Automate compliance across 35+ frameworks* Testkube: Leading test orchestration platform* Kameleoon: AI experimentation platform* Pendo: The #1 software experience management platform-----Key Takeaways1. N8N combines traditional workflow automation AND AI agent building in one platform - making it more powerful than Zapier or Make for complex automation needs.2. Real use cases span from simple business workflows to chatbots, automatic competitor monitoring, multi-agent research systems, and inbox workers that take actions based on emails. Sky is the limit.3. Pavel's competitor monitoring workflow costs $1-2/week using the FREE version of N8N. Just needs Perplexity API ($1-2 for hundreds of calls) and OpenAI credits. Enterprise tools charge $500+/month.4. Pin your data during development. N8N caches API responses so you don't burn credits while testing workflows. Click the pin icon and N8N uses cached data instead of making new API calls.5. N8N automatically loops through items - no need to write for-loops or while-loops. When you connect a node with 6 items, N8N repeats the action 6 times automatically.6. Compress context before sending to LLMs. Pavel cuts 70% of tokens by extracting only summary content and citation URLs from Perplexity results, ignoring irrelevant snippets and metadata.7. Use ChatGPT to write N8N code snippets. Pavel never writes code blocks himself - just takes a screenshot of the data and asks GPT "how do I compress this information?"8. Traditional workflows are more efficient (saves tokens, very reliable) for predictable tasks. AI agents are more flexible but use more tokens and can make mistakes. Use workflows when you know the steps.9. Set GPT reasoning effort to "low" for simple tasks. When you just need formatting or summarization (not complex thinking), low reasoning effort saves tokens significantly.10. Best practices: Set dedicated error probes to catch errors before they break workflows. Use max iterations to prevent infinite loops. Set retry on fail to 3x attempts. Pin data during development.-----Where to Find Pawel* LinkedIn* Newsletter* YouTube-----Related ContentNewsletters:* Ultimate Guide to AI Prototyping Tools* AI Agents: The Ultimate Guide for PMs* Practical AI AgentsPodcasts:* AI Agents Demo, with CEO of Relay.app* How to Build AI Agents (and Get Paid $750K+)* 5 AI Agents Every PM Should Build, with CEO of LindyIf you want access to a n8n competitor for free, get Aakash’s bundle and access to Relay.app.-----If you want to advertise, email productgrowthppp at gmail.

Today’s EpisodeLaura Burkhauser started as an IC PM at Descript, the $550M AI video editing platform.Three years later, she’s CEO.She shipped AI features that worked.In today’s episode, you’ll hear the exact features Laura built, the eval framework she used, and her complete IC → CEO path.This might be the most actionable career episode you listen to all year.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Maven: Improve your PM skills with awesome courses* Pendo: #1 Software Experience Management Platform* Vanta: Automate compliance across 35+ frameworks like SOC 2 and ISO 27001* NayaOne: Airgapped cloud-agnostic sandbox* Kameleoon: Leading AI experimentation platform----Key Takeaways1. Map your user journey BEFORE picking AI features. DeScript identified pain points (retakes, eye contact, rambling), then asked "what just became possible with LLMs?" Build that intersection.2. Build prepackaged buttons, not blank chat boxes. Each DeScript AI tool is a carefully crafted prompt behind a single button that delivers reliable results every time.3. Use human evals on production data before shipping. Test on real customer data, ask "would I use this as a customer?" If yes, ship. If no, don't.4. The ultimate metric is export rate. If users apply your AI feature then remove it before exporting, it didn't meet their quality bar.5. Switch from buttons to chat when you hit 30+ parameters. When users wanted topic selection, speaker choice, and platform optimization, chat became better than buttons.6. Match your eval data to actual use case. DeScript failed with Studio Sound because they tested on terrible audio (vacuuming, jackhammers) when real users had laptop microphones. Different models handle different quality levels.7. Test agents with real customer language early. Don't use toy data or employee terminology. Mix sophistication levels—some advanced at video and AI, some complete beginners—to understand how real people prompt.8. Launch AI agents to new users first. Video editing is hard and many people quit. DeScript tested Underlord on activation and it won, so new users got it first before existing users.9. Choose breadth over depth for product-wide agents. DeScript chose breadth—Underlord works across all features because "we're not a point solution." Requires more context, tool coverage, and evals but serves the product vision.10. Earn founder trust by getting command, not by being strategic. Use the product extensively. Talk to customers constantly. When you speak, people think "Smart" and invite you to more rooms. Ship features before focusing on strategy.----Where to Find Laura Burkhauser* LinkedIn* Company----Related ContentPodcasts:* AI Product Leadership Masterclass* Conversation with the CEO and Founder of Bolt* This $20M AI Founder Is Challenging Elon and Sam Altman | Roy Lee, CluelyNewsletters:* Ultimate Guide to AI Prototyping Tools* AI Agents: The Ultimate Guide for PMs* How to Land a $300K+ AI Product Manager JobPS. Please subscribe on YouTube and follow on Apple & Spotify. It helps! 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

Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Jira Product Discovery: Move discovery and roadmapping out of spreadsheets* Vanta: Automate compliance across 35+ frameworks like SOC 2 and ISO 27001* Kameleoon: Leading AI experimentation platform* NayaOne: Airgapped cloud-agnostic sandbox* Product Faculty: Get $500 off the AI PM Certification with code AAKASH25Today’s EpisodeClaude Code hit $1B ARR in 6 months. But OpenAI is not just giving up.ChatGPT’s new Codex is the most powerful way for product managers to build prototypes. And it’s a far better way to use ChatGPT than the browser.So every PM should know how to use it.Today, I brought back the man behind my Claude Code tutorial, Carl Vellotti, for a full guide on how to use ChatGPT Codex for PMs:This might be the most important podcast you watch all year. (And not a single other PM podcast has even talked about this tool)Your Newsletter Subscriber BonusFor subscribers, each episode I also write up a newsletter version of the podcast. Thank you for having me in your inbox.Today’s guide covers:* Getting Started: The Non-Technical PM’s Guide to Codex CLI* Classic PM Tasks: Documents, Meetings & PRDs with Codex* Advanced Prototyping: From Vibe Coder to Vibe EngineerThis is your complete Codex roadmap.1. How to Get Started - The Non-Technical PM’s Guide to Codex CLIIf you’ve never touched a terminal, this is for you.1a. Open Codex in an IDECarl opens Cursor and shows files Codex creates in real-time.Workflow: Open project folder in Cursor → Terminal (Control + backtick) → Type codex.Now you see files created, preview documents, navigate visually.As Carl Says:“Open it in an IDE. Easiest way to see what it’s actually doing.”1b. The YOLO Mode HackCodex asks for permission constantly—every website, every command.Solution:codex --yoloFull access mode. No prompts. Just execution.“Haven’t broken my computer yet. We’re in this directory so it won’t leave.”1c. Codex vs Claude CodeSame task on both: Search web, summarize differences.Claude Code: 3 searches simultaneously, ~2 minCodex: One site at a time, asks permissions, ~4 minClaude Code is faster, hides details. Codex shows every command—more verbose.“It’s Apple versus Microsoft. Claude does things in a nicer interface. Codex shows you everything.”2. How to Handle Classic PM Tasks with CodexCodex shines at daily PM work.2a. File Analysis Without UploadingRun Codex from a folder, it accesses everything. No uploading.Carl has demo folder (Taskflow) with interviews, notes, PRDs.“What user interviews completed?” → Codex lists them“Top 3 pain points?” → Returns: voice input reliability, integration gaps, template workflowCreates document with direct quotes—no manual file providing.2b. Template-Driven WorkflowsSolution: Create /templates folder with markdown files.Example: Discussion Points, Action Items, Risks & Blockers, Next StepsUse: Summarize @meeting-notes using @templateSame format every time. Works for PRDs, one-pagers, research summaries.2c. Socratic Questioning for Better PRDsProblem: Asking Codex to write a PRD produces garbage without proper thinking.Solution: Socratic template makes Codex ask YOU questions first.Questions: “Why is this helpful? Data, feedback, or strategic?” “What must work for V1?” “Edge cases?”You answer. AI embeds your thinking.Then Codex reviews context, templates, example PRDs, and writes.Carl: “Goes from kind of there to a really good PRD almost right out of the box.”3. Advanced Codex Techniques for Future Vibe EngineersThis is where Codex separates from the browser.3a. Design Systems with StorybookVibe coder problem: “Make title pink” → wrong shade → 20 iterations → still jankyVibe engineer solution: Storybook (npm run storybook)See components visually, change colors instantly, see changes live without redeploying.Carl changes recipe title to pink: read-only mode to see plan, then YOLO mode to execute. Updates in Storybook immediately.Pre-built components: Use Shadcn UI for production-grade React components. Calendar, date picker, dropdown—all done.“All the logic and difficult things, you get for free.”3b. Test-Driven Development is The UnlockProblem: AI says “Done!” but it’s broken. AI will lie and set variables to true to pass tests.Solution: Write tests BEFORE building.Red-Green-Refactor: Tests fail → Build until pass → Improve codeCarl’s macro calculator:Tests: API returns calories, empty recipe returns null, missing data shows “N/A”, API fails retries 3x, divide by servings correctlyTold Codex: “Build to make tests pass.”35 minutes. Zero touch. All tests green. Feature worked.Carl: “If you write tests FIRST, they can’t cheat.”3c. An Example - The TikTok Recipe BotCarl built this for his girlfriend: TikTok recipe extractor.Problem: Recipe videos on TikTok. No written recipe. Just “comment and I’ll DM.”Solution: Paste URL → Codex downloads video → Sends to Gemini (only model that processes video) → Gemini extracts recipe → Codex formats to PDFHow: Detailed implementation spec: architecture, data flow, APIs, error handling, retry logic, tests.Gave to Codex in GPT-5 Codex mode. Left 35 minutes.Built entire feature. Tests passed. Worked first try.Carl: “First time I saw the dream—give it a medium-sized feature and it just builds it.”Where to Find Carl Vellotti* Linkedin* X (Twitter)* Instagram* NewsletterRelated ContentPodcasts:* Claude Code Tutorial* Windsurf Tutorial* AI Prototyping TutorialNewsletters:* Ultimate Guide to AI Prototyping Tools* AI Agents: The Ultimate Guide for PMs* How to Land a $300K+ AI Product Manager JobPS. Please subscribe on YouTube and follow on Apple & Spotify. It helps! 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

Today’s EpisodeAI PM jobs pay 30-40% more than regular PM jobs.But here’s the problem: You can’t just slap “AI PM” on your resume.Todd Olson has spent 28 years in product management, VP of Product at a public company, then founder of Pendo, now a $2.5B product management platform working with everyone from American Cancer Society to Zendesk.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by - Reforge:Get 1 month free of Reforge Build (the AI prototyping tool built for PMs) with code BUILD----Key Takeaways1. AI PM market exploded - Last year 10% of PM jobs were AI PM jobs. This year it's 20%. They pay 30-40% more because of scarcity and skill level. But Todd warns: "You better damn well be good and know what you're talking about if you're gonna call yourself an AI PM because we are going to interrogate the hell out of it."2. Real requirement is production at scale - Not "I built prototype at 1-person startup." Hiring managers want 20,000 paying B2B customers experiencing your AI feature successfully. To get there: upskill internally at current company by shipping AI features on your roadmap.3. The 5-layer technical pyramid - Foundation: AI/ML fundamentals, data pipelines, prompt engineering. Middle: Observability (trace analysis), cost optimization, evals. Top: Product strategy, stakeholder management, leadership. You need to climb all 5 layers. Most PMs stop at layer 1.4. RAG is table stakes - "RAG is the de facto way to build." You ingest data, create embeddings, feed into vector database, look up relevant context, pass to LLM. Todd: "If you put too much in context window, just like a human, you get confused. You want to give the right context."5. PM-engineering tension is real - At startups, PMs do trace analysis. At large companies, engineering managers push back: "This is my world. I don't want some PM shadowing me." Similar to Data Dog—most PMs don't have login. Know the line. Be fluent but respect boundaries.6. But evals are YOUR domain - Unlike trace analysis, evals are where PMs are the expert. "The PM is probably the best-suited human being to author and manage eval sets." You understand user and business needs. Engineers don't have that context. This is must-have competency now.7. Cost optimization will matter - Some AI companies have sub-15% gross margins. Traditional software is 70-80%. Todd: "It's not a business at sub-15%." Eventually you'll rearchitect systems because infrastructure is too costly. Rule: when something's faster, it's cheaper (both buying compute).8. Solve hard problems, not shiny objects - Todd's test: "Are we gonna do much better job than ChatGPT out of box? Why would we just wrap that and slap Pendo logo on it?" His discovery agent example: hard part isn't interviewing customers—it's finding which to interview, prioritizing, scheduling. Automate that workflow.9. Kill bad features ruthlessly - Todd shipped features couple years ago that weren't great and turned them off. "Too often we hold on to something. Turn them off. Be unafraid. The more stuff in your product, the worse the experience is by default."10. Control the narrative with boards - Don't show up with no story and get crushed with random requests. Todd: "Show them how you actually run your business. I want to see what you're looking at, not something just made for me." Think deeply about how each bet drives shareholder value.----Where to Find Todd Olson* LinkedIn* Company* X----Related ContentPodcasts:* How to Become, and Succeed as, an AI PM | The Marily Nika Episode* If you only have 2 hrs, this is how to become an AI PM* Complete Course: AI Product ManagementNewsletters:* How to Become an AI Product Manager with No Experience* How to Write a Killer AI Product Manager Resume* How to become an AI Product Manager----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!----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

Today’s EpisodeThere are tons of tutorials about Claude Code and Cursor for IC PMs.But what about leaders?Today’s episode is a masterclass on both sides of AI product leadership. How to be a productive AI leader and how to ship AI-native features at scale.Rachel Wolan is the Chief Product Officer at Webflow, the $4 billion company powering TED Talks, SoundCloud, and Reddit.Rachel walks through building her agentic Chief of Staff live, sets up a LinkedIn post generator from scratch, and shares the brutal lessons from launching Webflow’s AI app generator.----Brought to you by:Linear: The task management platform dethroning Jira-----Key Takeaways:1. IC CPO means self-serving answers - "As a leader, you are able to get your own answers to practically any question." No waiting on data scientists. No back-and-forth with analytics. You have tools to self-serve insights, make analysis, automate workflows. Model behavior for your team to inspire them.2. Calendar agent analyzes time - Runs weekly with prompt: "Analyze my calendar for last two weeks. Where could I delegate?" Returns delegation opportunities, red flags (double bookings, context switching), what to cut next week. Rachel gives output to EA. Spot on when shown live.3. Email agent watches behavior - Complete inbox access. Runs triage, archives junk (calendar notifications, marketing), pins important messages, creates draft replies. Twist: watches behavior. If email sits too long, it notices. Caught meeting missing link. Rachel's rule: agent recommends, she approves. No autonomous sending.4. Analytics agent via MCP - Connected Claude Code to Snowflake via MCP servers (not officially supported repos, just fed them to Claude Code). Ask natural language questions, get SQL executed real-time. "How many sites does Shirts.com have?" Claude writes query, authenticates via SSO, returns answer. Data scientist in pocket.5. Accept the adoption curve - Your org follows standard curve: early adopters, early majority, late adopters, laggards. Create pathways for everyone to ascend ladder at their pace. Don't force everyone to be you. Rachel to team: "I only want to see prototypes when you have meetings with me." Creates culture investing in prototype quality.6. Builder Days strategy - Give everyone access: Claude Code licenses, MCP to Snowflake/Tableau, Figma Make, Cursor with design system. Run Builder Days where champions help others through technical hurdles. Everyone demos something outside comfort zone. Results: 0% to 30% of designers using Cursor weekly after first Design Builder Day.7. Rewrite career ladder - Webflow rewriting career ladder to make AI-native work an expectation, not nice-to-have. Create right incentives. Make sure people supported. Avoid AI for AI's sake. Example: Two designers built similar prototypes. Director caught early: "Go harmonize your prototypes now." Easier now than late in product cycle.8. MVO before MVP framework - Most teams: Feature → PRD → Design → Ship. Rachel flips it. MVO (Minimal Viable Output) before MVP. Get model's output right FIRST using RAG, prompt engineering, context engineering. Only then build feature. "If you don't have desired outputs, don't spend time productizing the AI feature."9. Evals are now your job - Brutal story: Webflow's AI app generator 2 weeks from launch. Rachel tested it. Agent kept dying. Realized: changed underlying model, evals didn't have coverage. Evals = test cases for models. Want dream evals (should pass) and edge cases (should fail). Use BrainTrust. Teaching PMs to write evals is part of AI PM toolkit now.10. Build on your strengths - Framework: See trend → Is it applicable to customers? → What's YOUR core competency? Webflow's strength: bringing visitors to front door via CMS. Built production-grade app generator (not prototype like Lovable). Uses your brand, CMS, hosting, security. "We're bringing a way to prompt an app to production." Don't copy trends, leverage unique strengths.-----Where to Find Rachel Wolan * LinkedIn* Website* X----Related Content* Claude Code Tutorial for AI PMs* AI Agents for PMs in 69 Minutes, with IBM VP* 5 AI Agents Every PM Should Build, with CEO of LindyNewsletters:* AI Evals Guide for PMs* Prompt Engineering for AI Agents* AI Agents: The Ultimate Guide for PMs----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps----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

Today’s EpisodeWhy do your prompts keep failing?You write the perfect prompt. The AI spits out garbage. You tweak. You iterate. You spend hours getting mediocre results.XK built Cues to $10M ARR in 60 days with zero VC funding and zero advertising. Today, he’s dropping the complete playbook:-----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:Reforge http://reforge.com/aakash-----Key takeaways:1. Context engineering beats prompting - One prompt won't work. Like hiring someone who knows nothing about your company—impossible to get results in 5 seconds. Accumulate context, build knowledge base, let AI know you over time. Combines system prompts, user prompts, memory, and RAG.2. The Mom analogy - Your mom knows your preferences, goals (grow taller for basketball), what makes you happy. She doesn't need detailed instructions. That's context engineering. AI that knows you creates better results and positive loops.3. Threads growth hack - Created hundreds of accounts posting use cases daily. Zero ad spend. Why it works: Threads gives traffic generously, less crowded than X, no creator hierarchy. Result: 3M impressions/month, hundreds of daily visits. Targeted Taiwan/Hong Kong markets.4. MVO before MVP - Traditional: Feature → PRD → Design → Ship. Xiankun's way: Get model output right FIRST. Use RAG, prompting, fine-tuning for Minimal Viable Output. Then productize. "If no desired outputs, don't spend time productizing."5. Visual context engineering - Use spatial tools: draw squares, graphs, sketches. AI understands spatial relationships. Unlike ChatGPT where files disappear, Kuse gives 2D space to store/reuse. Graphic operating system for AI that compounds.6. The pivot story - Started as design agent. Users uploaded documents instead. Knowledge base usage far exceeded design. Pivoted to horizontal knowledge-based AI. Listen to your users.7. Why X sucks for growth - Structured creator hierarchy. Can't farm traffic without famous connections. Good for VC fundraising, terrible for user acquisition. Threads and Instagram are underserved with real users.8. Compounding context power - Regular chatbots: one-off, context disappears. Kuse: processes files when you're away, pre-prepares everything. Like having ingredients ready vs ordering each time. Each interaction improves.9. Trading company origin - Co-founded YC company, created trading company, made money, funded Kuse with profits. Built without VC pressure. "Entrepreneurship is a game of focus." Building without chasing VC gives fresh perspective.10. Future vision: productivity playground - "Not building productivity tool, building playground." When AI takes jobs (2030-2040), people need fulfillment. Kuse is amusement park where people pretend to work, feel satisfaction. Going to pure pleasure, not efficiency.----Where to Find Xiankun Wu* LinkedIn* Threads* Company----Related ContentPodcasts:* We Built an AI Employee in 62 mins* Conversation with the CEO and Founder of Bolt* This $20M AI Founder Is Challenging Elon and Sam Altman | Roy Lee, CluelyNewsletters:* Context Engineering Guide* Prompt Engineering in 2025* How to become an AI Product Manager----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!----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

Today’s EpisodeThe salary for AI PMs is skyrocketing.Hamza Farooq works with companies like Home Depot, Trip Adviser, and Jack in the Box on their AI strategy. He teaches AI PM courses at Stanford, UCLA, and Maven.Today, he’s giving you the complete 6-month roadmap to go from no experience to PM at OpenAI or Anthropic.We built a live AI prototype in 30 minutes (with RAG and agents working). And Hamza breaks down the exact technical skills you need to master.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Maven* Amplitude: The market-leader in product analytics* Vanta: Leading AI compliance platform* NayaOne* Kameleoon: Leading AI experimentation platform----Key Takeaways:1. AI PM salaries are skyrocketing - The median total comp for AI PMs is rapidly increasing. But now you need technical depth. Previously, you didn't need to know what RAG is or how fine-tuning works. Now you have to be a jack of all trades.2. We built a working prototype in 30 minutes - Live demo: Lovable for front-end + n8n for workflow automation + RAG connected and working. What used to take days now takes minutes. This is the power of modern AI PM tools.3. Context engineering is more important than prompt engineering - Prompt engineering is what you tell an LLM. Context engineering is how you design the instructions. You combine: system prompt, user prompt, memory (long-term), and RAG. This enables true personalization.4. Know the difference: fine-tuning vs RAG - Fine-tuning = adding new vocabulary (new words). RAG = adding new knowledge (new information). Use RAG for knowledge that changes frequently. Use fine-tuning for vocabulary or specialized response patterns.5. The 5-step architecture you need to master - Step 1: Understand what LLMs are. Step 2: Learn how to build applications. Step 3: Master prompt engineering. Step 4: Implement RAG systems. Step 5: Build agentic systems. Follow this roadmap on repeat.6. Use the three-wave approach for building - Wave 1: Save time (efficiency gains). Wave 2: Better quality (better output). Wave 3: Completely new (novel capabilities). Start with time-savers, progress to quality improvements, end with breakthrough innovations.7. Ask yourself 3 questions before building anything - Does it solve a user problem? Does it solve an organizational problem? Does it align with your business model? If yes to all three, build it. This validates every project.8. Build-first mentality wins - Don't just follow roadmaps. Keep building things. You have to learn by doing. The best way to become an AI PM is to build 10+ projects and see where your products fit in solving real business problems.9. Real-world example: Traversal.ai - Hamza's company works with manufacturers (Amazon suppliers, Jack in the Box, Home Depot). They built an army of agents processing 20,000 SKUs daily with demand forecasts. Results: better inventory optimization, planning, and cost savings.10. Teaching accelerates your own growth - Hamza makes 10-15% of revenue from Maven courses. Why keep teaching? "I teach because I grow." His foundation course builds empathy with users. His developer course uplifts his technical skills by working on real problems with senior engineers.----Where to Find Hamza Farooq* LinkedIn* NewsletterRelated ContentPodcasts:* Google AI PM Director drops an AI PM Masterclass* If you only have 2 hrs, this is how to become an AI PM* Complete Course: AI Product ManagementNewsletters:* How to Become an AI Product Manager with No Experience* How to Write a Killer AI Product Manager Resume* How to become an AI Product Manager----PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps!----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

Today’s EpisodeEvery PM needs to master AI prototyping in 2025.But which tool should you use? And how do you actually prototype effectively?Alex Danilowicz built Magic Patterns to $1M in revenue in 6 months. Today, we’re putting his tool against the competition live.We built the same prototype in 5 different tools and graded each one. Then Alex shared the exact workflow his customers use.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:Vanta: Leading AI compliance platformTestkube: Leading test orchestration platformKameleoon: Leading AI experimentation platformJira Product Discovery: Plan with purpose, ship with confidenceThe AI PM Certificate: Get $550 off with ‘AAKASH550C7’----Key Takeaways1. Different tools for different jobs - Magic Patterns excels at visual prototyping, user research, and design system integration. V0/Replit/Bolt excel at full-stack functionality, real APIs, and backend. We tested 5 tools live—V0 won (3.7 GPA), Magic Patterns second (3.6 GPA).2. Define your end goal before opening any tool - Sharing with customers = need design system. Internal validation = skip brand context. Alex's mistake in our face-off? He jumped into building without setting up his preset and wasted time retrofitting ChatGPT's Agent Kit styling later.3. Set up your design system in 5 minutes - Magic Patterns Chrome extension grabs components from Storybook, production sites, or Figma. Click "Convert to Component" and it's available in every prompt. Converts HTML to Tailwind automatically. 5 minutes upfront saves hours later.4. Gather context before prompting - Don't start with blank prompts. Common sources: Jira tickets, PRDs, competitor screenshots, customer feedback. Power users use ChatGPT/Claude to write their Magic Patterns prompts first.5. Use select mode for iterations - Vague prompts waste time. Bad: "Make it better." Good: "Move toast to top-left and make it green." Always click the exact element you want to change. The AI can't read your mind.6. The new product development workflow - Old: Write PRD → Align stakeholders → Build → Pray. New: Build prototype (30 min) → Share link → Test with customers → Iterate → Write PRD with learnings → Build validated solution. Cuts 15+ meetings down to 1.7. AI prototyping cuts failure rates in half - 80% of features don't hit their metrics. You're building blind. With prototypes, you validate: usability, viability, value, drop-offs, corner cases. Before: only test biggest features. Now: test every feature.8. Break out of doom loops - Pattern to avoid: "Doesn't work" repeated 10 times. Repeating the same prompt makes it worse. Use Magic Patterns' /debug command or restart with clearer prompt. Read the AI's output—it's having a conversation.9. Master the 4-step workflow - Step 0: Define end goal. Step 1: Set up design system (if needed). Step 2: Gather context (PRDs, screenshots). Step 3: Iterate specifically with select mode. This workflow helped Magic Patterns hit $1M revenue in 6 months.10. Know when to use each tool - Magic Patterns finished first in speed with best iteration quality. Replit prompted for OpenAI key (more functionality). Use Magic Patterns for: user validation, testing interactions. Use V0/Replit for: backend, real APIs, deployable prototypes.----Where to Find Alex Danilowicz* LinkedIn* Twitter/X* Website----Related ContentPodcasts:* Cursor Tutorial* Windsurf Tutorial* AI Prototyping TutorialNewsletters:* 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

Today’s EpisodeWhy do some AI products feel like magic while others feel like work?You shipped. It works. Your metrics show “success.”But users aren’t coming back. They’re not telling friends. And next quarter, they’ll switch to the competitor with a better model.Nesrine Changuel built Spotify Wrapped and ran Google’s Delight Team. Today, she’s giving you the complete playbook:The 4-step Delight Model to engineer emotional connection (not just satisfaction)----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Miro: The AI innovation workspace* Vanta: Leading AI compliance platform* Testkube: Leading test orchestration platform* Kameleoon: Leading AI experimentation platform* The AI PM Certificate: Get $550 off with ‘AAKASH550C7’-----Key Takeaways01 | Understand the 3 Types of DelightLow Delight solves functional needs only. Surface Delight adds emotion without function (confetti, animations). Deep Delight combines both - solving problems while creating emotional connection. ChatGPT and Cursor win because they nail Deep Delight. Most PMs only ship Low Delight.02 | Follow the 50-40-10 RuleAllocate 50% of your roadmap to Low Delight (core functionality), 40% to Deep Delight (differentiation), and 10% to Surface Delight (brand personality). Deep delight drives 2x retention, 2x referrals, and 2x revenue versus satisfied users. This is your competitive moat.03 | Start with Motivational SegmentationStop segmenting by demographics. Identify WHY users actually use your product. Map functional motivators (search, get inspired) AND emotional motivators (feel less lonely, feel proud). Your users aren't all using your product for the same reason.04 | Use the Delight GridCreate a grid with functional motivators on vertical axis and emotional on horizontal. Place every feature idea on it. Only functional = Low Delight. Only emotional = Surface Delight. At the intersection = Deep Delight. Can't map it? Don't build it.05 | Apply the Humanization TechniqueAsk: "If my product was a human, how would the experience be better?" Google Meet compared to being in the same room, not Zoom. Dyson compares to hiring a human cleaner, not competitors. This creates features like hand raise and emoji reactions.06 | Validate with the Delight ChecklistBefore shipping, ask: Does it bring value to business AND user? Is it inclusive? Is it familiar? Is it continuous? Is it measurable? Google Meet held back filters until they worked on ALL skin tones. This prevents Apple's breakup message disaster.07 | Study Deep Delight ExamplesGmail Smart Compose reduces stress while helping you write. Google Meet's AI translation uses YOUR voice and emotion. Spotify's Discover Weekly personalizes while creating belonging. Chrome's Inactive Tabs improves performance while respecting user relationships. Function + emotion together.08 | Test for Corner Cases ObsessivelyApple's AI summarized a breakup as "no longer in relationship, wants belongings." WhatsApp told a grieving person to "ask John to resend" a photo of her deceased brother. AI progresses fast functionally, but emotional needs get ignored. Corner cases destroy reputations.09 | Learn from ChatGPT's WinChatGPT has 800M users not because of accuracy. People pay subscriptions because they feel less lonely. The emotional need - companionship for solo founders and remote workers - drives retention. Deep delight = personalization that improves over time and remembers context.10 | Start Delight Early, Not LaterDon't say "let me ship functionality first, add delight later." You're building brand perception from day one. Users forgive functional gaps if the experience delights. They won't forgive boring products that work. Engineer delight from the start.----Where to Find Nesrine Changuel* LinkedIn* Twitter/X* Product Delight Book----Related ContentPodcasts:* How to Use Google’s Latest AI Tools* What it means to be Design-Led* If you only have 2 hrs, this is how to become an AI PMNewsletters:* How to Build AI Products Right* How to Land a $300K+ AI Product Manager Job* How to Become an AI Product Manager with No Experience----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

Today’s EpisodeAlex Reachvky has helped hundreds of PMs land $700K+ AI jobs.The gap between $140K and $700K isn’t magic. It’s method.Today, he breaks down the exact AI-powered workflow to land an AI PM job, from resume creation to acing interviews.This is the playbook PMs are using right now to 10X their callbacks and land multiple offers.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:Brought to you by Linear: Plan and build products like the best.----Key Takeaways1. AI PM jobs pay 30-40% more than regular PM roles - Group PMs make $360K-$600K, CPOs make $2M+. In 2025, 20% of PM roles now mention AI (up from 2% in 2023). The market is exploding and compensation bands are wider than ever.2. Your resume's top 3 lines are everything - Recruiters spend 7 seconds scanning for Impact, Scope, and Recognizability. Template: "[X years] PM at [Google] | [2B users] | [Scaled revenue 50% YoY to $3.5B]." Pack your biggest wins and recognizable brands here.3. Create a "bullet vault" then customize in 5 minutes - Use AI to transform your raw career dump into structured bullets covering all PM skill bundles. Use this master resume to tailor for each role by extracting 3-5 non-generic must-haves from the JD.4. Cold applications get 1% callbacks, outreach gets 10-15% - The math: 30-100 apps → 3-4 callbacks → 1 interview. For every role, find the hiring manager, recruiter, and senior PM. Use ContactOut for emails. Message formula: 1 intro + 3 bullets + 1 CTA under 150 words.5. Follow up on days 2, 3, and 5 - People miss emails. Persistence wins jobs. If no email response, send LinkedIn connection request. The golden age of PM networking is here: send 30 connection requests daily, comment on posts for 10X more reach than posting.6. Use Whisper to brain dump at 200 WPM - Answer 24 career questions by speaking instead of typing at 120 WPM. Cover: projects, impact, obstacles overcome, tools introduced, people mentored. This becomes your career vault for both resumes and behavioral interview stories.7. Behavioral interviews follow Hook-Principles-Action-Results-Learnings - Build 10-15 stories covering leadership challenges, stakeholder conflicts, failed projects, launches. Practice progression: Written first → Spoken → Timed (under 3 minutes). Feed to AI for refinement and probing follow-ups.8. Case interviews are evaluated on 6 dimensions - Structured Thinking, User Focus, Product Sense, Prioritization, Communication, Creativity. Prompt AI: "You're a FAANG interviewer. Ask me ONE question. Rate 1-5. Quote my weak phrases, explain why they failed, give better approach."9. Only apply when 50%+ aligned with the role - Extract non-generic must-haves from the JD using AI. Ignore "team player" fluff. Focus on: specific tech infrastructure, growth levers, scale requirements. Rewrite top 3 lines and stack rank bullets to match. Don't let AI fabricate experience.10. Build your target company list strategically - AI prompt: "Create 50-100 companies ranked by fit. Consider: size (public/late-stage/early-stage), interests, geography." Keep broad. More interviews = better negotiation leverage. Focus on roles posted in last 24 hours. Most PM jobs still in SF Bay/Seattle.----Where to Find Alex Rechevskiy* LinkedIn* Twitter/ X* Website----Related ContentPodcasts:* Google AI PM Director drops an AI PM Masterclass* If you only have 2 hrs, this is how to become an AI PM* Complete Course: AI Product ManagementNewsletters:* How to Become an AI Product Manager with No Experience* How to Write a Killer AI Product Manager Resume* How to become an AI Product Manager----PS. 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

Every PM is asking the same question: Which AI tools actually make me faster?There are hundreds of apps. Most are hype. Some are game-changers.Today, I sat down with Anshumanni Rudra - VP of Product at Hotstar, now Group Product Manager at Google leading all APAC payments - to rank 70+ AI tools tier-list style.We didn’t hold back. S-tier tools got crowned. D-tier tools got exposed.And we revealed the single best AI tool for product managers in 2025.Watch the full episode for a chance to win a 1-year free subscription to my newsletter.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* Miro: The innovation workspace* Vanta: Leading AI security & compliance platform* Testkube: Leading test orchestration platform* Kameleoon: Leading AI experimentation platform* Dovetail: abc----Key Takeaways1. Claude Code is the absolute best AI tool for PMs - Anshumanni runs 6 terminal windows simultaneously doing different things on different parts of his directory. It understands your entire codebase and lets you go from idea to working code in minutes.2. superwhisper is the S-tier dictation tool that has Anshumanni shouting debugging commands at his screen like Tony Stark. His typing speed has actually fallen since he started dictating everything, making typing feel obsolete.3. Lindy.AI is the S-tier agent builder PMs actually want because you can prompt it with natural language instead of building flows. Create email responders, meeting prep assistants, and podcast-to-blog converters without touching code.4. Replit is the ultimate AI prototyping champion that can plan and work for hours building complete applications with minimal guidance. Even before AI, Replit was a strong web-based IDE with deep developer understanding that shows.5. Granola is the S-tier meeting tool that learns your style and auto-generates talking points based on previous conversations. Unlike Otter or Fireflies, it has intelligent context awareness like a personal assistant.6. Perplexity gets C-tier as Anshumanni's usage has "gone down quite drastically" since the early days. AI mode in other tools now does what Perplexity used to do with deep search rabbit holes.7. Cursor gets A-tier as the only IDE with the agent on the right side of the screen, which matters for how PMs think. Anshumanni's usage is "way higher" than other tools purely because of this UX choice.8. Bolt is Anshumanni's pick for best AI prototyping in A-tier with the best structure from the start. It thinks about both front-end and back-end by default, letting you go from prompt to deployed app in minutes.9. GitHub Copilot is the first D-tier tool because it's "just not as good" - very ChatGPT focused, not enough Claude. Developers are leaving for Cursor and Claude Code for a reason.10. Don't chase shiny tools - analyze how you spend your week, find what takes the most time, then find the specific tool that solves that problem. Pick tools for your workflow, experiment, then measure if they improve productivity.---Related ContentPodcasts:* How to Use Google’s Latest AI Tools | Jaclyn Konzelmann Episode* How to PM Production Changes with Devin | Sahil Lavingia Episode* Complete Course: AI Product ManagementNewsletters:* How to Become an AI Product Manager with No Experience* How to Write a Killer AI Product Manager Resume----Want my coaching to your dream AI PM job? Apply to grab one of the remaining 17 seats in my cohort:P.S.1 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.P.S.2 I’d really appreciate ratings + reviews on podcast platforms as well.----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

I had a precious hour of a Google AI PM Director’s time. So, I extracted all the best insights about AI PM for you:How to use Google’s latest AI tools like an insiderHow to build great AI productsHow to become an AI PMAnd I didn’t hold back on the tough questions. And Jaclyn Konzelmann dropped an absolute masterclass.You don’t want to miss her advice on AI PM resumes...----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:Vanta. Pendo. Linear Generic. Jira Product Discovery.* Vanta: Leading AI security & compliance platform* Pendo:* Linear: Plan and build products like the best.* Jira Product Discovery: Plan with purpose, ship with confidence* LandPMJob: Land a PM Job with Aakash Gupta----Key Takeaways1. Nano Banana Understands World Models: Ask it to show Toronto in winter → adds snow. San Francisco in winter → no snow. The model knows SF doesn't get snow. This world knowledge unlocks creative workflows beyond basic image generation.2. The Colorization Workflow: Use Gemini Pro to refine prompts → Focus on vibrant colors, lighting transformation, hyperrealistic detail, modern camera optics → Add negative prompts for failed iterations. "Keep playing around with things until you get it just right."3. Chain Tools for Advanced Workflows: Photo → Imagen (reimagine as drone show) → Veo (animate the drones flying) → Result: Your pet as a living drone show with tail wagging. Access through AI Studio, Gemini app, or Mixboard.4. Build AI Apps Without Code Using Opal: Describe what you want in natural language → Opal writes the prompt chains → Customize models and outputs → Share publicly. Examples: Resume critique tool, nature collage generator, custom storybook maker.5. The Anatomy of an Agent Framework: Every AI agent has 3 components - Models (text/image/video capabilities), Tools (APIs, search, UI actions), Memory (what to remember, personalization strategy). Define these before writing code or PRDs.6. The User Interaction Spectrum: Every AI product falls on "Do it FOR me" (Deep Research, Audio overviews that run and return) vs "Do it WITH me" (vibe coding, interactive experiences).7. The Inverted Triangle: Think Big, Ship Fast: Think REALLY big → Use 3 levers to ship: Scope (ruthless MVP cuts), Positioning (beta/experiment labels), Audience (internal → trusted testers → public). Don't let process slow the vision.8. Ask The Paradigm Shift Question: Are you building a faster horse or a car? Process-improving a workflow or creating an entirely new one? "The real value is the unlock on what's the new way things will get done."9. The Future-Proofing Question: What happens when models get better? Real example: Mixboard threw out months of image editing work when Nano Banana launched with natural language editing.10. Google's 6 Hiring Criteria for AI PMs: Exceptional product taste, visionary leadership (think 5 steps ahead), clarity in chaos, compelling product storytelling, full-spectrum execution (blended role profiles), deep AI intuition. Keep resume to 1 page, show actual work, design with personality.11. The Side Project Strategy: Run 10 side projects simultaneously. Not to launch 10 products, but to think differently and connect dots.12. Don't Get Precious About Ideas: Any single idea can get commoditized in weeks with AI. The skill isn't having one great idea—it's consistently generating good ideas.----Where to Find Jaclyn Konzelmann* X (Twitter)* Linkedin* Substack----Related ContentPodcasts:* How to Become, and Succeed as, an AI PM | The Marily Nika Episode* If you only have 2 hrs, this is how to become an AI PM* Complete Course: AI Product ManagementNewsletters:* How to Become an AI Product Manager with No Experience* How to Write a Killer AI Product Manager Resume* How to become an AI Product Manager----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

Today’s EpisodeSam Altman said one person will build a billion-dollar company.Sahil’s already halfway there with just one employee.Most PMs are still running 6-week sprints. Writing 10-page PRDs. Coordinating between designers and engineers. Sahil ships features from Slack to production in 30 minutes.Here’s the exact AI workflow powering Gumroad’s $10M ARR:If AI gets it wrong, your communication was unclear.----Check out the conversation on Apple, Spotify, and YouTube.Brought to you by:* Vanta: Leading AI security & compliance platform* Testkube: Leading test orchestration platform* Kameleoon: Leading AI experimentation platform* The AI PM Certificate: Get $550 off with ‘AAKASH550C7----Key Takeaways1. Three-Tier AI Workflow: Small tasks (Slack → Devon → Production), Medium tasks (GitHub issue → GPT for PRD → V0 prototype → Ship), Large tasks (4-line brief → V0/Codex → Vercel → Cursor → Production). Match the tool to task complexity.2. From Slack to Production in Minutes: Customer reports feature request in Slack with screenshots. Type "Devon, address this." Devon reads thread, writes code, opens PR, ships to production. "Weeks of coordination at big companies. We just decide and Devon addresses it."3. The PRD Is Dying: Stop writing 20-page PRDs for AI. Write 4 lines. Let AI prototype. See what it misunderstands. That reveals what you forgot to specify. "The PRD is only as dense as what cannot be inferred naturally."4. Use AI to Refine Your Thinking: Paste brief into V0, GPT, and Codex. Each builds something different. Their mistakes show your communication gaps. It's a fake conversation with engineers that makes your real spec better.5. Architecture Is the New Competitive Advantage: Gumroad is deleting 5,425 lines of CSS to migrate to Tailwind (181 lines). Global CSS means every change affects 300 files. Tailwind means one file change. "Devon made a one-file change. With CSS, you're testing 300 files."6. Tailwind Is Built for AI: Design system in 181 lines: fonts, colors, padding, borders, shadows. AI never guesses. Industry standard with massive training data. "It's like hiring an engineer who already understands 2x4s. AI knows exactly what to do."7. AI Is 99th Percentile at Most Things: Defer design and code decisions to AI. If it's important, put it in the spec. If not in the spec, let AI decide. "The decisions AI makes are pretty good. That's why we can move super fast."8. Work on 5 Things Simultaneously: AI is slow. Solution? Run 4-5 AI sessions at once. While V0 builds, check email. While Codex compiles, answer Slack. "It's like having an army of assistants. I don't wait—I fill the dead time."9. The Dictatorship Advantage: Big companies need buy-in from PMs, designers, engineers, managers. Gumroad: Sahil → Devon → Production. "The hard part at big companies is aligning people to get behind a decision. It has nothing to do with actually shipping."10. Perfect the Business, Don't Scale It: $10M ARR, $7-8M EBITDA, $2M dividends last year, 1 employee, 35,000 creators. Goal: $10M EBITDA, then perfect the software. "I just want to work on software, make it better, have people use it, be proud of the work we do."----Where to Find Sahil Lavingia* Linkedin* X (Twitter)* Gumroad----Related ContentPodcasts:* We Built an AI Employee in 62 mins* Conversation with the CEO and Founder of Bolt* This $20M AI Founder Is Challenging Elon and Sam Altman | Roy Lee, CluelyNewsletters:* How to Build AI Products Right* Ultimate Guide to AI Prototyping Tools* The Fintech Super App Wars----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