The Growth Podcast

Today’s episodeThe market is looking tough for non-technical PMs.Every single week, my comments look exactly the same: brilliant product managers who have the vision, specs, and roadmap in mind, but have zero coding skills. They want to build, and while thousands of technical resources exist online, they make a flawed assumption: that you already know how to code.So when I invited Andre Albuquerque on my podcast, I had to ask him to share his setup. Andre is the founder of Builders Camp, a product school with 4,000+ students across 30 countries, who runs five businesses with Claude Code and has never been a developer.Live on the episode, he built a fully functional product from scratch to show how easily a non-technical PM can go from 0 to 1. He also walked me through CLAUDE.md architecture, custom multi-agent skills, and the bridge between Lovable and Claude Code (which, by the way, not many people are talking about).If you have been putting off Claude Code because it feels too technical or intimidating to set up, this episode is absolutely for you.----Check out the conversation on Apple, Spotify, and YouTube.Brought to you by:* Customer.io —* Amplitude — The market-leader in product analytics* Bolt — Ship AI-powered products 10x faster* Arize — Ship AI agents and features faster, with fewer regressions* Product Faculty — Get $550 off their #1 AI PM Certification with code AAKASH550C7----* If you want access to my AI tool stack - Dovetail, Arize, Linear, Descript, Reforge Build, Relay.app, Magic Patterns, Speechify, Bolt.new and Mobbin - become an annual subscriber ($150), and grab Aakash’s bundle.* If you want access to my AI PM customizations - PM OS, Job Search OS, and Prompt Library - become a founding subscriber ($250).----Key Takeaways:1. Non-technical PMs are stuck in Jira, Linear, and PowerPoints - Most European PMs are still product owners in disguise, paper-shuffling between strategy and engineering teams. The way out is to actually start building, not to lobby for more autonomy.2. Start with Lovable on a personal project - Build something for your family, your friends, yourself. The codebase does not need to be pretty. The point is the safety to make mistakes without breaking anything that matters.3. The Lovable + Claude Code bridge nobody documents - Connect both tools to the same GitHub repo. Write code in Claude Code with all its depth. QA visually in Lovable with its hosted preview. Publish from Lovable's button. The perfect transition layer.4. Lovable, Cursor, and Vercel are not competitors - Lovable bundles the IDE, the hosting, and the deployment in one product. Vercel exposes the hosting layer so you can run real branches with real preview URLs. Cursor is just an IDE with a generous free tier.5. Cursor has a free debugging agent - When Claude Code breaks, open a Cursor agent and paste the error. The free agent unsticks you instead of leaving you stuck at step zero.6. CLAUDE.md is your team's culture - Loaded automatically every session. The first rule should be "for every task, call the PM agent." When you notice yourself fixing the same issue twice, update CLAUDE.md so it never happens again.7. The PM agent never writes code - The PM orchestrator's only job is to decide which other agent should handle the work. The researcher investigates. The designer proposes. The engineer architects. The implementer writes.8. Do not copy famous people's skills wholesale - Going on LinkedIn and downloading 100 skills from product celebrities creates more confusion than value. Look at how your real team works. Write each role down as an agent.9. Fix the agent, not the feature - When something ships wrong, do not patch the output. Identify which agent in the pipeline failed, update its instructions, and run the pipeline again. The next session inherits the fix.10. The Monday morning move is exactly three steps - Get added as a collaborator on a low-risk repo. Pick the oldest ticket in the backlog. Push a branch and demo by Friday.----Related contentPodcasts:* Claude Code and agents with Gabor Meyer* n8n, Claude Code, and OpenClaw with Mahesh Yadav* Claude Code with Hannah StulbergNewsletters:* How to Build a Full AI Dev Team* How to Become a Builder PM* How to build a Team OS in Claude CodeP.S. Reply with “CLAUDE” and I’ll send you Andre’s actual CLAUDE.md template. He said we could share it.PS 2. 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 EpisodeDesigning with AI isn’t about prompting.Most PMs think they understand AI design because they can write a good prompt. They’re wrong.Real AI design is about understanding the entire workflow, the system, the constraints, and the behaviors.Xinran Ma runs Design with AI, one of the top newsletters on AI design. He’s been studying AI design tools for three years. And he hasn’t shared most of this information publicly before.In today’s episode, we’re going live. We’re building real prototypes. We’re showing you the exact workflows that top 1% designers use.By the end of this episode, you’ll know the entire workflow from PRD to prototype to product.----Check out the conversation on Apple, Spotify and YouTube.Brought to you by:* NayaOne: Airgapped cloud-agnostic sandbox* Pendo: The #1 software experience management platform* Maven: The cohort-based course platform powering the future of learning* Bolt: Ship AI-powered products 10x faster* Gamma: Turn customer feedback into product decisions with AI----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.----Key takeaways:Key Takeaways:1. AI design covers five areas not just prompts - Prompting, ideation, design/prototyping, workflows, and staying conscious. Most people think better prompts equal better design. That's just 20% of the skill.2. Use Google AI Studio for quick design variations - Upload 2-3 visual references. Describe what you want. Generate three different design directions in 5 minutes. What used to take 3-4 hours now takes 15 minutes.3. Lovable builds functional prototypes in seconds - Describe the experience you want to build. Lovable generates a working prototype in 60 seconds. Not mockups—actual clickable experiences you can test with users.4. Match tools to specific use cases - Custom GPT for effective prompts. Lovable for high-quality prototypes. Magic Patterns for design variations. Google AI Studio for free exploration. Cursor for full-stack experiences. Claude Code as all-purpose best.5. Good design passes four layers not just visual - Visual representation, problem-solving, design principles, and implementation feasibility. Most people stop at layer one. Great design works at all four layers.6. Context matters more than prompt length - Don't say "design a button." Say "design a primary CTA button for B2B SaaS onboarding where users connect calendar. Professional brand." Specificity drives quality.7. Visual references anchor AI output - Upload 2-4 screenshots showing the aesthetic you want. These show AI what "modern and minimal" means to you. The quality difference is massive versus text-only prompts.8. Iteration speed determines final quality - The magic isn't in the first output. It's in the 10th iteration after you've refined and tweaked. Review, identify issues, tell AI how to fix, repeat.9. Always validate with real users - AI tools make generating designs easy. Only users tell you if those designs actually help. Show prototypes to 3-5 users. Watch them try to use it.10. Workflows changed from linear to parallel - Before AI: sequential steps taking weeks. After AI: describe, generate, iterate freely. This is how top 1% designers work now.----Where to Find Xinran* LinkedIn* Newsletter* Maven courseRelated ContentNewsletters:* AI Prototyping Tutorial* AI Prototype to Production* How to Build AI Products* Prompt Engineering* Product Requirements DocumentsPodcasts:* Advanced Guide to AI Prototyping with Sachin Rekhi* 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 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 EpisodeDiscovery might be the most important core PM skill for building great products.But most PMs are unprepared to do discovery in AI. PMs run surveys incorrectly, conduct interviews poorly, and end up with poor insights.Today will give you the roadmap to avoid all those mistakes.Caitlin Sullivan is a user research expert who runs courses teaching PMs how to do AI-powered discovery. And in today’s episode, she shows you exactly how she does it.We’re talking live demos. Step-by-step workflows. Real survey data. Real interview transcripts.This is a masterclass in discovery. The kind that moves the needle.----Brought to you by:Maven: Get 15% off Caitlin’s courses with code AAKASHxMAVENPendo: The #1 software experience management platformJira Product Discovery: Plan with purpose, ship with confidenceKameleoon: AI experimentation platformAmplitude: The market-leader in product analytics----Key Takeaways:1. Replicate the human process - Good AI analysis mirrors how experienced researchers work: comb through data first, then synthesize. Never jump straight to "give me themes."2. Use multi-step prompting - Load context in one prompt, run per-participant analysis in the next, then verify. Cramming everything into one prompt degrades quality.3. Code before you count - For surveys, apply inductive coding labels to every response before asking for patterns. Skipping this step leads to miscategorized, unreliable results.4. Always audit AI's work - Force the model to re-check its own analysis. It catches contradictions, overexaggerated intensity ratings, and miscoded responses regularly.5. Claude wins on nuance, Gemini wins on frequency - Claude gives more thorough, complete analysis by default. Gemini surfaces top-frequency themes faster but misses smaller patterns.6. Define everything explicitly - Quotes, ratings, emotional intensity levels, contradiction types. If you assume the model shares your definitions, you'll get inconsistent results.7. Markdown files beat raw transcripts - Converting transcripts to structured markdown improves accuracy and helps you work around token limits on non-Max plans.8. Parallelize with Claude Code agents - Set up agent markdown files for interview and survey analysis, then run both simultaneously. Cuts total analysis time in half again.----Related ContentNewsletters:How to Do Product Discovery RightAdvanced Techniques: Continuous DiscoveryCustomer Interviews: Advanced TechniquesPodcasts:Teresa Torres’ Guide to AI DiscoveryComplete Course: AI Product DiscoveryUltimate Guide to Knowing Your Users as a PM----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 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 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 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

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.