How I AI

• How to turn meeting notes into prototypes that your sales team can immediately demo to customers | Anjan Panneer Selvam (Acolyte Health)

  Anjan Panneer Selvam is the Chief Product and Technology Officer at Acolyte Health, where he’s pioneering the use of AI across the entire product development lifecycle. In this episode, he demonstrates how AI tools can dramatically accelerate alignment between stakeholders, reduce development time from months to minutes, and enable teams to validate ideas with customers before committing engineering resources.What you’ll learn:1. How to transform meeting transcripts into interactive prototypes in under 30 minutes using ChatGPT, Lovable, and other AI tools2. A step-by-step workflow for creating market analyses and competitive research in minutes instead of days3. How to build a “living product library” that allows sales and customer success teams to demo prototypes to customers before engineering begins4. Techniques for using AI to break deadlocks with engineering by demonstrating what’s possible without requiring technical expertise5. Why AI enables faster stakeholder alignment by converting abstract ideas into tangible, interactive experiences6. How to use ChatPRD to validate product requirements and ensure you’ve considered all critical aspects before engaging engineering—Brought to you by:Notion—The best AI tools for work: https://www.notion.com/howiaiLovable—Build apps by simply chatting with AI: https://lovable.dev/—Where to find Anjan Panneer Selvam:LinkedIn: https://www.linkedin.com/in/anjanps/—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to Anjan(02:36) How AI changes the relationship between product and engineering(04:08) Workflow for converting stakeholder ideas into prototypes(08:50) Using the Limitless pendant to capture meeting transcripts(12:45) Creating interactive prototypes with Lovable(15:57) Benefits of using prototypes instead of documentation(19:07) Conducting market research with Perplexity(21:45) Creating presentation decks with Gamma(23:08) AI doesn’t replace PMs; it elevates them(25:05) Using ChatPRD to validate product requirements(29:10) Building a living product library for sales and customer success(35:50) Breaking deadlocks with engineering using Rork for mobile prototypes(39:00) Takeaways for building with AI(42:34) Cultural implications of AI in product development(45:20) Strategies for when AI doesn’t give you what you want—Tools referenced:• ChatGPT: https://chat.openai.com/• Lovable: https://lovable.dev/• Limitless: https://www.limitless.ai/• Perplexity: https://www.perplexity.ai/• Gamma: https://gamma.app/• ChatPRD: https://www.chatprd.ai/• Rork: https://rork.com/• v0: https://v0.dev/• Magic Patterns: https://www.magicpatterns.com/—Other references:• React Flow: https://reactflow.dev/• Figma: https://www.figma.com/• Acolyte Health: https://acolytehealth.com/• Meta Ray-Ban glasses: https://www.ray-ban.com/usa/ray-ban-meta-ai-glasses—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  48:32

  --------

  48:32
• How to digest 36 weekly podcasts without spending 36 hours listening | Tomasz Tunguz (Theory Ventures)

  Tomasz Tunguz is the founder of Theory Ventures, which invests in early-stage enterprise AI, data, and blockchain companies. In this episode, Tomasz reveals his custom-built “Parakeet Podcast Processor,” which helps him extract value from 36 podcasts weekly without spending 36 hours listening. He walks through his terminal-based workflow that downloads, transcribes, and summarizes podcast content, extracting key insights, investment theses, and even generating blog post drafts. We explore how AI enables hyper-personalized software experiences that weren’t feasible before recent advances in language models.What you’ll learn:1. How to build a terminal-based podcast processing system that downloads, transcribes, and extracts key insights from multiple podcasts daily2. A workflow for using Nvidia’s Parakeet and other AI tools to clean transcripts and generate structured summaries of podcast content3. How to extract actionable investment theses and company mentions from podcast transcripts using AI prompting techniques4. A systematic approach to generating blog post drafts with AI that maintains your personal writing style through iterative feedback5. Why using an “AP English teacher” grading system can help improve AI-generated content through multiple revision cycles6. How to leverage Claude Code for maintaining and updating personal productivity tools with minimal friction—Brought to you by:Notion—The best AI tools for workMiro—A collaborative visual platform where your best work comes to life—25k giveaway: To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway—Where to find Tomasz Tunguz:Blog: https://tomtunguz.com/Theory Ventures: https://theory.ventures/LinkedIn: https://www.linkedin.com/in/tomasztunguz/X: https://x.com/ttunguz—In this episode, we cover:(00:00) Introduction to Tomasz Tunguz(03:32) Overview of the podcast ripper system and its components(05:06) Demonstration of the transcript cleaning process(06:59) Extracting quotes, investment theses, and company mentions(10:20) Why Tomasz prefers terminal-based tools(12:38) The benefits of personalized software versus off-the-shelf solutions(15:31) A workflow for generating blog posts from podcast insights(17:34) Using the “AP English teacher” grading system for blog posts(18:25) Challenges with matching personal writing style using AI(22:00) Tomasz’s three-iteration process for improving blog posts(26:13) The grading prompt and evaluation criteria(28:16) AI’s role in writing education(30:28) Final thoughts—Tools referenced:• Whisper (OpenAI): https://openai.com/research/whisper• Parakeet: https://build.nvidia.com/nvidia/parakeet-ctc-0_6b-asr• Ollama: https://ollama.com/• Gemma 3: https://deepmind.google/models/gemma/gemma-3/• Claude: https://claude.ai/• Claude Code: https://claude.ai/code• Gemini: https://gemini.google.com/• FFmpeg: https://ffmpeg.org/• DuckDB: https://duckdb.org/• LanceDB: https://lancedb.com/—Other references:• 35 years of product design wisdom from Apple, Disney, Pinterest, and beyond | Bob Baxley: https://www.lennysnewsletter.com/p/35-years-of-product-design-wisdom-bob-baxley• Dan Luu’s blog post on latency: https://danluu.com/input-lag/• GitHub CEO: The AI Coding Gold Rush, Vibe Coding & Cursor: https://www.readtobuild.com/p/github-ceo-the-ai-coding-gold-rush• Stanford Named Entity Recognition library: https://nlp.stanford.edu/software/CRF-NER.html—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  35:14

  --------

  35:14
• Using Veo 3 to create AI-generated music videos, like a Tiny Desk Concert with Notorious B.I.G. and Kurt Cobain

  Anish Acharya is an entrepreneur and general partner at Andreessen Horowitz, focusing on consumer investing and AI-native products. In this episode, he demonstrates how AI can be used for creative and personal projects beyond typical work applications. He walks through creating an AI-generated Tiny Desk Concert for Notorious B.I.G. and Kurt Cobain, building a book cataloging app using video analysis, and using browser automation for personal finance insights. Anish shares how these technologies allow anyone to bring creative ideas to life with minimal technical expertise, transforming what would have been impossible projects just a few years ago into accessible weekend activities.What you’ll learn:1. A step-by-step workflow for creating AI-generated music videos featuring artists like Kurt Cobain and Notorious B.I.G.2. How to extract vocals from existing tracks to create unique audio combinations for your AI-generated videos3. A simple method for cataloging your book or record collection using video analysis and Gemini Flash4. How to use Comet to analyze personal finances and get investment recommendations without manual data analysis5. Ways AI is transforming childhood learning and play by enabling interactive storytelling and creative exploration—Brought to you by:Notion—The best AI tools for workLenny’s List on Maven—Hands-on AI education curated by Lenny and Claire—Where to find Anish Acharya:• Andreessen Horowitz: https://a16z.com/author/anish-acharya/• LinkedIn: https://www.linkedin.com/in/anishacharya/• X: https://x.com/illscience—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(⁠00:00⁠) Introduction to Anish Acharya(⁠03:05⁠) How AI transforms creative constraints in music and video(⁠06:00⁠) Creating an AI-generated Notorious B.I.G. Tiny Desk Concert(⁠07:36⁠) Using GPT-4o to generate still images(⁠09:27⁠) Using Hedra to animate still frame images(⁠10:40⁠) Adding custom audio to video(⁠11:30⁠) Using Adobe Audition to clip and sync audio(⁠15:42⁠) How to use Demucs to extract vocals from any song(⁠16:36⁠) Using Hedra to generate a Tiny Desk Concert featuring Kurt Cobain(⁠19:40⁠) Creating a ’90s-style Nirvana music video with Veo 3(⁠27:40⁠) Building a book collection cataloging tool with Gemini Flash(⁠35:35⁠) Using the Comet browser for personal finance analysis(⁠37:20⁠) How AI is transforming childhood learning and play(⁠41:23⁠) Tips for getting better results from AI tools—Tools referenced:• GPT-4o: https://openai.com/index/hello-gpt-4o/• Hedra: https://www.hedra.com/• Adobe Audition: https://www.adobe.com/products/audition.html• Demucs: https://github.com/facebookresearch/demucs• Perplexity: https://www.perplexity.ai/• Veo 3: https://deepmind.google/models/veo/• Kapwing: https://www.kapwing.com/• Cursor: https://cursor.com/• Google AI Studio: https://makersuite.google.com/• Gemini Flash: https://ai.google.dev/gemini-api• Comet: https://www.perplexity.ai/comet—Other references:• Anish’s Notorious B.I.G. AI-generated Tiny Desk Concert: https://x.com/illscience/status/1935721063876550939• NPR Tiny Desk Concerts: https://www.npr.org/series/tiny-desk-concerts/• Notorious B.I.G.: https://en.wikipedia.org/wiki/The_Notorious_B.I.G.• Kurt Cobain: https://www.kurtcobain.com/• Robinhood: https://robinhood.com—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  43:00

  --------

  43:00
• How Amplitude built an internal AI tool that the whole company’s obsessed with (and how you can too) | Wade Chambers

  Wade Chambers, Chief Engineering Officer at Amplitude, shares how his team built Moda—an internal AI tool that gives employees access to enterprise data across multiple systems, enabling faster product development and decision-making while fostering cross-functional collaboration.What you’ll learn:1. How Amplitude built a powerful internal AI tool in just 3 to 4 weeks of engineers’ spare time2. A social engineering approach that made their AI tool go viral company-wide in just one week3. How product managers use AI to analyze customer feedback across multiple data sources and identify key themes4. A streamlined workflow that compresses research, PRD creation, and prototyping into a single meeting5. Why role-swapping exercises with AI tools build empathy and cross-functional fluency across product, design, and engineering teams6. How AI tools are helping engineering teams tackle persistent tech debt challenges more effectively—Brought to you by:CodeRabbit—Cut code review time and bugs in half. Instantly.Vanta—Automate compliance and simplify security—25k giveaway: To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway.—Where to find Wade Chambers:LinkedIn: https://www.linkedin.com/in/wadechambers/Amplitude: https://amplitude.com/blog/meet-the-team-wade-chambers—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to Wade Chambers(02:53) The build vs. buy decision for internal AI tools(04:55) What Moda is and how it works(07:19) The social engineering approach to adoption(09:17) Demo of Moda in Slack(10:58) Data sources Moda has access to(12:43) Analyzing customer feedback themes with Moda(17:41) Behind the scenes: how Moda works technically(23:24) Creating a PRD from a single customer insight(27:30) How teams actually use AI-generated PRDs(29:09) Impact on product development velocity(32:37) Engineers, designers, and PMs swapping roles(34:38) Recap of creating Moda(36:00) Lightning round and final thoughts—Tools referenced:• Glean: https://www.glean.com/• ChatGPT: https://chat.openai.com/• Cursor: https://cursor.com/• Bolt: https://bolt.new/• Figma: https://www.figma.com/• Lovable: https://lovable.dev/• v0: https://v0.dev/—Other references:• Amplitude: https://amplitude.com/• Slack: https://slack.com/• Confluence: https://www.atlassian.com/software/confluence• Jira: https://www.atlassian.com/software/jira• Salesforce: https://www.salesforce.com/• Zendesk: https://www.zendesk.com/• Google Drive: https://drive.google.com/• Productboard: https://www.productboard.com/• Zoom: https://zoom.us/• Asana: https://asana.com/• Dropbox: https://www.dropbox.com/• GitHub: https://github.com/• HubSpot: https://www.hubspot.com/• Abnormal Security: https://abnormalsecurity.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  40:26

  --------

  40:26
• An exclusive inside look at GPT-5

  In this episode, I share my hands-on experience with OpenAI’s GPT-5, the company’s new frontier model. As one of the first users outside of OpenAI to test the model, I put GPT-5 head-to-head with GPT-4.1 across real-world product use cases—from writing PRDs to generating code to assisting with visual design work. This is my unfiltered look at what GPT-5 can (and can’t) do—and how it changes the game for builders.What you’ll learn:1. How GPT-5 differs from previous models with its engineering-focused approach to problem-solving and tendency to prioritize technical details over business context2. A comparative analysis of how GPT-5 and GPT-4.1 generate different types of product requirement documents and prototypes for the same prompt3. Why GPT-5 excels at technical writing, functional requirements, and code generation while potentially skipping important business discovery questions4. The model’s impressive spatial awareness capabilities when generating images for interior design and other visual tasks5. Practical considerations for choosing the right model based on your specific use case and audience6. How GPT-5’s extensive tool-calling behavior and bullet-point communication style reflect its engineering-oriented design—Brought to you by ChatPRD—an AI copilot for PMs and their teams: https://www.chatprd.ai/howiai—25k giveaway: To celebrate 25,000 YouTube followers, we’re doing a giveaway. Win a free year of my favorite AI products, including v0, Replit, Lovable, Bolt, Cursor, and, of course, ChatPRD, by leaving a rating and review on your favorite podcast app and subscribing to the podcast on YouTube. To enter: https://www.howiaipod.com/giveaway—Where to find Claire Vo:ChatPRD: https://www.chatprd.ai/Website: https://clairevo.com/LinkedIn: https://www.linkedin.com/in/clairevo/X: https://x.com/clairevo—In this episode, we cover:(00:00) Introduction to GPT-5(04:34) Testing GPT-5 in ChatPRD for document generation(07:10) Comparing GPT-5 and GPT-4.1 on business vs. technical orientation(11:22) Side-by-side comparison of PRDs generated by both models(15:23) Where GPT-5 excels: Technical considerations and documentation quality(17:35) Comparing prototypes generated from different model outputs(19:57) Testing homepage critique capabilities between models(23:14) OpenAI’s strengths in API design and developer support(25:37) GPT-5’s performance as a coding assistant(27:26) Examining GPT-5 in ChatGPT’s interface(28:50) Testing GPT-5’s front-end design capabilities(31:17) Personal use case: bathroom remodel planning(33:45) Comparing GPT-5 vs. GPT-4 for interior design visualization(38:10) Summary of key findings and recommendations—Tools referenced:• OpenAI: https://openai.com/• ChatGPT: https://chat.openai.com/• Claude: https://claude.ai/• Gemini: https://gemini.google.com/• Cursor: https://cursor.sh/• v0: https://v0.dev/• Lovable: https://lovable.dev/• Bolt: https://bolt.com/• LaunchDarkly AI Configs: https://launchdarkly.com/docs/home/ai-configs—Other reference:• Benjamin Moore paints: https://www.benjaminmoore.com/—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].

  --------  

  40:11

  --------

  40:11

Więcej Technologia podcastów

Trendy w podcaście Technologia

O How I AI