The Growth Podcast

Aakash Gupta
  • 4.7 (35)
  • TECHNOLOGY
  • UPDATED SEMIWEEKLY

Join 65K+ other listeners in the worlds biggest podcast on AI + product management. Host Aakash Gupta brings on the world's leading AI PM experts. www.news.aakashg.com

  1. 1D AGO

    Gemini Gem Masterclass From the Creator Lisa Huang

    Today’s episode Most PMs are using AI the same way they used Google in 2005. Type something in. Get something out. Move on. That is not how the best PMs are using it. The best PMs have stopped treating AI as a search engine and started treating it as a team member. One that already knows their product, their writing style, their strategy. One that does not need to be briefed from scratch every single time. That shift is what today’s episode is about. I sat down with Lisa Huang, SVP of Product at Xero, an $18 billion finance platform. She built the AI assistant for the first generation Meta RayBan smart glasses. She created Gemini Gems at Google. She has been an AI PM at Apple, Meta, and Google - three of the most demanding AI product environments in the world. She gave us a masterclass across Gemini Gems, building AI into hardware, running AI agents at scale inside a financial product, and what the AI PM career actually looks like from here. In today’s episode, we discuss across three topics. * How to build Gemini Gems and AI projects that actually work. * What she learned building AI into a wearable device. * What the future of the AI PM career actually looks like. ---- 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 ---- 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: 1. Stop briefing your LLM from scratch every time - Gemini Gems hold your context permanently. Your role, your company strategy, your writing style. Build it once and it already knows everything the next time you open it. 2. Every PM needs 3 Gems - A writing clone trained on your PRDs and emails. A product strategy advisor loaded with your company docs and competitor analysis. A user research synthesizer that ingests raw transcripts and surfaces key themes. 3. Vague instructions are the number one mistake - "Help me write better" gets you nothing. Write a full page of context. Your role, your audience, your format preferences. The more specific, the more personalized the output. 4. Gemini Gems vs ChatGPT custom GPTs - OpenAI framed GPTs as an app store ecosystem. Google focused on personal productivity instead. First principles beat copying a competitor's framing, and the GPT store never took off. 5. On-device AI is the future for wearables - Cloud is the default today but once a device is on your face all day, people want their data staying local. Privacy beats performance when the device is that personal. 6. Accuracy is the product in high-stakes AI - LLMs out of the box are not great at math, accounting, or tax. Winning agents combine deep domain knowledge with proprietary data that no general-purpose model can access. 7. Measure agents in three layers - Quality first (evals, human annotators, LLM judges). Product metrics second (adoption, retention, CSAT). Business impact third (revenue attribution, ARR). Skip to layer three without the foundation and you are measuring on sand. 8. AI will not replace PMs - it will replace the execution work. Writing PRDs, creating mocks, managing roadmaps. What stays is product judgment. The ability to look at ambiguous signals and say this is the right bet and here is why. 9. The PM role is becoming a hybrid - PM to engineer ratios will compress. The expectation is that PMs also build. Not just spec and hand off, but prototype, design, and code enough to show what they mean. The tools to do this exist right now. 10. Your company's permission is not required - Most companies are not fine-tuning models. They are using the same consumer tools you already have. Build Gems. Build projects. Build small AI products with your personal data. There is nothing stopping you. ---- Where to find Lisa Huang * LinkedIn * Website Related content Newsletters * How to become an AI PM * Practical AI agents for PMs * AI evals explained simply * AI product strategy * The AI PM learning roadmap Podcasts * Claude Code + Analytics - Vibe PMing with Frank Lee * AI evals explained simply with Ankit Shukla * How to become an AI PM with Marily Nika * AI prototyping mastery with Sachin Rekhi ---- 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

    52 min

  2. FEB 27

    How to AI Prototype Well | Masterclass from $5.5B Founder, Nadav Abrahami (Wix)

    Today’s episode AI prototyping tools are redefining what it means to be a PM. Bolt went from 0 to $40M ARR in 4.5 months. Lovable hit $17M ARR in 3 months. Every forward-thinking product team is starting to prototype earlier, faster, and at higher fidelity than ever before. But most PMs are using these tools wrong. They open Bolt or Lovable, type a vague prompt, get something that looks decent, show it around, and move on. No problem space work. No divergent solutions. No user testing. The prototype dies in a Slack thread and nothing changes. In this episode, we built a LinkedIn sentiment analysis feature from scratch - live - to walk you through the complete workflow. From blank page to multi-page, clickable, high-fidelity prototype. We covered when to prototype, how to prompt, when to go high fidelity, and how to hand off to engineers with zero open questions. If you watch, you’ll also learn why your PRD and prototype need to live together - and why that combination is the new standard for forward-thinking PMs. ---- Check out the conversation on Apple, Spotify and YouTube. Brought to you by: * Pendo: The #1 software experience management platform * Testkube: Leading test orchestration platform * Gamma: Turn customer feedback into product decisions with AI * Product Faculty: Get $550 off the AI PM Certification with code AAKASH550C7 * Mobbin: Discover real-world design inspiration ---- 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: 1. AI prototyping doesn't replace problem space work - it accelerates solution space work. Before opening any prototyping tool, lock down the problem, the user story, and the rough shape of the solution. If you can't write all three in one paragraph, you're not ready. 2. Always start from your design system, not a blank page - Drop a screenshot of your existing product and ask the tool to recreate it. Save that as a team template. Every prototype you build from that point looks like it belongs in the product. 3. Build 3 to 4 divergent solutions before choosing one - The entire point of AI prototyping is that building a second and third version costs almost nothing now. We built two versions of the sentiment analysis feature live. Neither was perfect. Both were useful. That comparison is the point. 4. Use visual editing for fine-tuning, not prompting - Once you've picked the strongest direction, switch to direct visual editing. Move elements, match colours with the eyedropper, adjust spacing. It's faster because the result is immediate. 5. Single-page prototypes miss too much - Build the full end-to-end flow. The moment you start connecting pages, edge cases surface automatically. We found two edge cases in minutes that would have cost engineering time in sprint. 6. Prompt clarity beats prompt engineering - Any ambiguity in your prompt will get exploited statistically. Before running a complex prompt, paste it into a separate chat and ask it to find the contradictions. Fix those first. 7. Use discuss mode before building anything major - Don't ask the AI if it can do something. That always gets a yes. Ask what it thinks the right approach is. The answer is far more honest and useful. 8. High fidelity is for selling and usability testing - Low fidelity is for team exploration. Any prototype going in front of users needs to feel real, otherwise you get feedback about the roughness, not the experience. 9. The PRD and prototype should live together - The PRD covers edge cases, empty states, error conditions. The prototype covers the 90% flows. Together they leave zero open questions for engineers. If someone reads both and still has a question, something is missing. 10. The prototype is already standard code - A functional prototype built in Dazzle is a full server-side and client-side application. Download the project folder, drop it next to the production codebase, and tell Cursor to copy the interaction. Most of the implementation gets handled automatically. ---- Related content Newsletters * Product Requirements Documents (PRDs): a modern guide * Ultimate guide to AI prototyping tools (Lovable, Bolt, Replit, v0) * Your guide to AI product strategy * AI PRDs: everything you need to know * AI agents: the ultimate guide for PMs Podcasts * The most powerful AI workflow for PMs with Frank Lee * How to engineer delight into AI products with Nazarin Shenel * AI prototyping tools with Eric Simons, CEO of Bolt ---- 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

    1h 17m

  3. FEB 25

    Claude Code + Analytics = Vibe PMing

    Today’s episode There is a term Andrej Karpathy coined last year: vibe coding. We have the same for product management: Vibe PMing. You describe the problem. The agent pulls the data. Analyzes the chart. Synthesizes the feedback. Drafts the spec. Files the ticket. That is not theory. That is what I walked through in today’s episode with a principal PM at Amplitude who builds MCP and agent products for a living. He showed it live, on screen, in real time. If you tune in, you’ll learn the full end-to-end workflow: ---- 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. ---- Check out the conversation on Apple, Spotify and YouTube. Brought to you by: * Amplitude: The market-leader in product analytics * Pendo: The #1 software experience management platform * Testkube: Leading test orchestration platform * Product Faculty: Get $550 off the AI PM Certification with code AAKASH550C7 * Bolt: Ship AI-powered products 10x faster ---- Key Takeaways:1. Claude Code + MCP is the most powerful AIPM workflow today - Connect your analytics tool via MCP, load your product context into a repo, and let the agent do analysis that used to take hours in minutes.2. Deep chart analysis now takes 90 seconds instead of 3 hours - Drop a chart URL into Claude Code, trigger the analyse chart skill, and the agent navigates your data taxonomy, finds anomalies, and hypothesises why metrics changed.3. Automate your entire weekly business review - Point Claude Code at your dashboards Monday morning. Get 3-5 top insights and the one urgent issue to tackle — no manual dashboard scanning ever again.4. Customer feedback synthesis across all channels in one pass - Zendesk, Gong, Salesforce, Slack, app stores all unified. Claude Code navigates the MCP, clusters themes, and surfaces what customers love and hate that week.5. PRDs write themselves from insights - Take the analysis output, point it at your PRD template in Cursor or Claude Code, and get a first draft spec in under 2 minutes. Iterate with command L or command K.6. Skills are the most important Claude Code feature - A skill is just a named prompt with heuristics and tool instructions. It loads only when relevant, preventing context bloat and giving the agent a repeatable workflow.7. The biggest MCP mistake is connecting too many servers - Every tool description burns context. Load only what's relevant to the workflow. Remove or hide tools that aren't being used for a given task.8. MCP is not for complex orchestration — it's for data access - Set the right expectation. MCP connects AI to external systems easily. It's the first step, not the whole pipeline.9. Granola has no MCP, so build a script instead - Frank used Claude Code to write a local script that dumps Granola meeting notes into his product repo. Now he can pull all meeting context with a single at-command.10. The future of PMing is vibe PMing - Chart analysis, dashboard reporting, feedback synthesis, spec writing, and prototyping — all agent-driven. PMs who adopt this workflow now will have a massive advantage in 2-3 years. ---- Related content Newsletters: * How to use Claude Code like a pro * Steal 6 of my Claude skills * Context engineering * The AI stack for PMs * Practical AI agents for PMs Podcasts: * How to build an AI-native PM operating system with Mike Bal * AI evals explained simply with Ankit Shukla * Advanced guide to AI prototyping with Sachin Rekhi PS. 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

    53 min

  4. FEB 21

    How to Design with AI | The Complete Guide for PMs with Xinran Ma

    Today’s Episode Designing 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 course Related Content Newsletters: * AI Prototyping Tutorial * AI Prototype to Production * How to Build AI Products * Prompt Engineering * Product Requirements Documents Podcasts: * 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

    1h 2m

  5. FEB 19

    AI Evals Explained Simply by Ankit Shukla

    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 Today’s Episode Ankit Shukla is BACK after his gangbusters episode, that is my #2 most popular of all time. This time he's diving deep on one of the most important new AI skills for PMs: Evals. Whether you're working on AI features now or not, this is a skill you want to have an intuitive understanding of. So, I'm building on my library of eval episodes with today's drop. I've never heard someone explain evals from first principles as intuitively as Ankit has with this one. Hope you enjoy as much as I did! 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. Where to find Ankit Shukla * HelloPM * Twitter (X) * LinkedIn * YouTube Related Content Newsletters: * AI Evals * AI Testing * LLM Judges Podcasts: * How to Do AI Evals Step-by-Step with Real Production Data * The PM’s role in AI Evals * AI Evals Live PS. Please subscribe on YouTube and follow on Apple & Spotify. It helps! email productgrowthppp at gmail dot com for sponsorships. 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

    1h 4m

  6. FEB 13

    How to Do AI-Powered Discovery (Step-by-Step with Live Demo) | Caitlin Sullivan

    Today’s Episode Discovery 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 AAKASHxMAVEN Pendo: The #1 software experience management platform Jira Product Discovery: Plan with purpose, ship with confidence Kameleoon: AI experimentation platform Amplitude: 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 Content Newsletters: How to Do Product Discovery Right Advanced Techniques: Continuous Discovery Customer Interviews: Advanced Techniques Podcasts: Teresa Torres’ Guide to AI Discovery Complete Course: AI Product Discovery Ultimate 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

    1h 13m

  7. FEB 3

    How to Build An AI Native PM Operating System with Mike Bal, Head of Product at David's Bridal

    Today’s Episode Most 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 Content Newsletters: * AI Product Strategy * How to Build AI Products * AI Agents for PMs * Product Requirements Documents Podcasts: * 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! 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

    1h 1m

  8. JAN 29

    AI Agent Browsers: Should you use one? | ChatGPT Atlas vs Perplexity Comet vs Arc Dia

    Today’s Episode ChatGPT 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 Content Newsletters: * AI Product Strategy * How to Build AI Products * AI Prototyping Tutorial * How to Become an AI PM * Ultimate Guide to Onboarding Podcasts: * 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

    58 min
See All (129)

4.7
out of 5
35 Ratings

About

Join 65K+ other listeners in the worlds biggest podcast on AI + product management. Host Aakash Gupta brings on the world's leading AI PM experts. www.news.aakashg.com

Information

  • Creator
    Aakash Gupta
  • Years Active
    2024 - 2026
  • Episodes
    129
  • Rating
    Clean
  • Copyright
    © Aakash Gupta
  • Show Website
    The Growth Podcast

You Might Also Like