How I AI

Claire Vo
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How I AI, hosted by Claire Vo, is for anyone wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will share a specific, practical, and impactful way they’ve learned to use AI in their work or life. Expect 30-minute episodes, live screen sharing, and tips/tricks/workflows you can copy immediately. If you want to demystify AI and learn the skills you need to thrive in this new world, this podcast is for you.

  1. How to get your whole team excited about AI (and actually using it) | Brian Greenbaum (product designer at Pendo)

    -19 Ч

    How to get your whole team excited about AI (and actually using it) | Brian Greenbaum (product designer at Pendo)

    Brian Greenbaum is a Senior Staff Product Designer at Pendo who led a company-wide AI transformation after a personal epiphany while on paternity leave. After experiencing the power of AI coding tools firsthand, he created a structured approach to help his entire product organization adopt AI. In this episode, Brian shares his complete playbook for driving AI adoption across teams, measuring success, and navigating the organizational challenges that come with new technology adoption. What you’ll learn: The exact Slack message Brian sent while on paternity leave that kickstarted his company’s AI transformationHow to structure both synchronous and asynchronous AI learning opportunities for maximum adoptionThe two-pronged approach that dramatically increased AI tool usage across teamsWhy becoming your company’s AI champion is one of the best career moves you can make right nowHow to measure AI adoption success with sentiment surveys and clear metricsThe critical role of creating a “golden path” for AI tool usage with legal, security, and finance teams— Brought to you by: Google Gemini—Your everyday AI assistant Lovable—Build apps by simply chatting with AI — In this episode, we cover: (00:00) Introduction to Brian Greenbaum (01:38) Brian’s paternity leave epiphany that sparked an AI initiative (05:00) Sending the message that launched a transformation (12:25) The two-pronged approach: synchronous and asynchronous learning (17:29) Encouraging experimentation and creative exploration (18:41) How AI enables designers to move beyond MVP thinking (22:00) Quick summary of the two-pronged approach (24:43) Measuring AI adoption (33:48) Creating a centralized AI knowledge center (35:58) Building an MCP server to demonstrate AI’s potential (44:08) Why technical understanding is crucial for non-technical roles (46:01) Final thoughts — Tools referenced: • Cursor: https://cursor.com/ • Bolt.new: https://bolt.new/ • Claude: https://claude.ai/ • ChatGPT: https://chat.openai.com/ • Midjourney: https://www.midjourney.com/ • Gemini: https://gemini.google.com/ — Other references: • Pendo: https://www.pendo.io/ • Confluence: https://www.atlassian.com/software/confluence • Slack: https://slack.com/ — Where to find Brian Greenbaum: LinkedIn: https://www.linkedin.com/in/briangreenbaum/ — 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 — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    48 мин.
  2. How Zapier’s EA built an army of AI interns to automate meeting prep, strengthen team culture, and scale internal alignment | Cortney Hickey

    15 ДЕК.

    How Zapier’s EA built an army of AI interns to automate meeting prep, strengthen team culture, and scale internal alignment | Cortney Hickey

    Cortney Hickey is the executive assistant to the CEO at Zapier, where she’s leveraging AI to transform traditional EA responsibilities into scalable, organization-wide systems. In this episode, she demonstrates how she’s built AI workflows that automate meeting preparation, reinforce company culture through automated feedback, and democratize strategic knowledge across the organization. Her approach shows how EAs can use AI not to replace their roles but to elevate them—working on higher-impact initiatives while creating systems that benefit the entire company. What you’ll learn: How to build an automated meeting prep system that researches participants, checks CRM data, and delivers actionable insights before important meetingsA framework for creating AI-powered culture reinforcement through automated meeting feedback aligned with company values and operating principlesHow to develop an AI-powered document review system that helps teams align with executive expectations before formal reviewsA strategy for creating a centralized knowledge base that makes company strategy accessible and interactive for all employeesWhy “progress over perfection” is the key mindset for building effective AI workflows that evolve over timeHow EAs can use AI automation to work themselves out of repetitive tasks and into higher-impact strategic roles— Brought to you by: WorkOS—Make your app enterprise-ready today Brex—The intelligent finance platform built for founders — In this episode, we cover: (00:00) Introduction to Cortney (02:48) Overview of meeting prep automation with Zapier Agents (04:43) How the meeting prep agent works (10:21) An example of the meeting prep agent in practice (12:16) Creating a culture reinforcement system through meeting feedback (15:45) EAs’ unique position to leverage these tools (18:12) Building an automated meeting coach (24:03) Developing an executive document review system (33:15) Creating a centralized strategy companion in NotebookLM (36:18) How AI is transforming the EA role, not replacing it (40:00) Lightning round and final thoughts — Tools referenced: • Zapier: https://zapier.com/ • Zapier Agents: https://zapier.com/agents • Todoist: https://todoist.com/ • Slack: https://slack.com/ • HubSpot: https://www.hubspot.com/ • ChatGPT: https://chat.openai.com/ • Google NotebookLM: https://notebooklm.google/ — Where to find Cortney Hickey: LinkedIn: https://www.linkedin.com/in/cortneyhickey/ — 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 — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    45 мин.
  3. ChatGPT agent mode: The “little helper” that transformed recruiting, crafted user personas, and solved parking nightmares | Michal Peled (Honeybook)

    8 ДЕК.

    ChatGPT agent mode: The “little helper” that transformed recruiting, crafted user personas, and solved parking nightmares | Michal Peled (Honeybook)

    Michal Peled is a Technical Operations Engineer at HoneyBook who specializes in building internal tools and automations that eliminate friction for teams. In this episode, Michal demonstrates three practical AI use cases: using ChatGPT’s agent mode to automate LinkedIn recruiting, transforming customer research into interactive AI personas, and creating a custom calendar solution for a very San Francisco–specific problem—avoiding expensive parking during Giants games. What you’ll learn: How to use ChatGPT agent mode to automate LinkedIn recruiting and find high-quality candidates that manual searches missedThe step-by-step process for turning static customer research into interactive AI personas that product and marketing teams can actually useWhy NotebookLM excels at creating prompts from source material with proper citationsHow to structure agent-mode prompts to create effective “little helpers” that follow your exact workflowA practical framework for improving your prompts when AI tools aren’t giving you the results you wantHow internal tools teams can drive massive impact by focusing on eliminating friction in everyday workflows— Brought to you by: Brex—The intelligent finance platform built for founders Google Gemini—Your everyday AI assistant — In this episode, we cover: (00:00) Introduction to Michal and ChatGPT agent mode (02:10) Using agent mode for LinkedIn recruiting automation (05:14) Creating effective prompts for agent mode (10:50) Demo of agent mode searching LinkedIn profiles (16:29) Results and team reception of the recruiting automation (19:53) The outcome of implementing on Michal’s team (23:50) Creating custom GPT personas from customer research (28:43) Using NotebookLM to transform research into persona prompts (35:00) Adding guardrails to custom GPT personas (37:20) Demo of interacting with custom-persona GPTs (41:02) Creating a calendar automation for parking during baseball games (48:15) Lightning round and final thoughts — Tools referenced: • ChatGPT: https://chat.openai.com/ • NotebookLM: https://notebooklm.google.com/ • Claude: https://claude.ai/ — Other references: • Google Calendar: https://calendar.google.com/ • HoneyBook: https://www.honeybook.com/ • LinkedIn: https://www.linkedin.com/ — Where to find Michal Peled: LinkedIn: https://www.linkedin.com/in/michalpeled/ — 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 — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    59 мин.
  4. Gemini 3 vs. Claude Opus 4.5 vs. GPT-5.1 Codex: Which AI model is the best designer?

    3 ДЕК.

    Gemini 3 vs. Claude Opus 4.5 vs. GPT-5.1 Codex: Which AI model is the best designer?

    I put three cutting-edge AI models to the test in a head-to-head design competition. Using the exact same prompt, I challenged Google’s Gemini 3, Anthropic’s Opus 4.5, and OpenAI’s Codex 5.1 to redesign my blog page, evaluating them on visual design quality, user experience improvements, and SEO optimization capabilities. One model produced a beautiful, polished, production-ready redesign. One was fine. And one completely whiffed. If you’re trying to figure out where each model fits in your workflow—design, planning, back-end, or something else—this episode will save you a lot of trial and error. What you’ll learn: How each AI model approaches the same design challenge differentlyWhy planning capabilities dramatically impact design qualityThe specific visual and functional improvements each model madeWhich model excels at front-end design versus back-end functionalityHow to strategically choose the right AI model for different parts of your workflowThe importance of model-switching based on specific use cases— Blog design: https://www.chatprd.ai/blog — Brought to you by: Lovable—Build apps by simply chatting with AI — 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 the AI design challenge (01:25) The question: Which model is the better designer? (03:08) The prompt used for all three models (04:10) Gemini 3 Pro’s approach and results (06:00) Opus 4.5’s approach and results (10:54) Codex 5.1’s approach and disappointing results (14:51) Comparing the three designs side by side (16:03) Analyzing the change logs and SEO improvements from each model (22:43) Final verdict (23:00) Conclusion and next steps — Tools referenced: • Gemini 3 Pro: https://deepmind.google/models/gemini/pro/ • Anthropic Opus 4.5: https://www.anthropic.com/news/claude-opus-4-5 • OpenAI Codex 5.1: https://platform.openai.com/docs/models/gpt-5.1-codex • Cursor: https://cursor.com/ — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    25 мин.
  5. “PMs who use AI will replace those who don’t”: Google’s AI product lead on the new PM toolkit | Marily Nika

    1 ДЕК.

    “PMs who use AI will replace those who don’t”: Google’s AI product lead on the new PM toolkit | Marily Nika

    Marily Nika, AI Product Lead at Google and founder of the AI Product Academy, demonstrates how product managers can leverage AI tools to dramatically accelerate their workflow. Using a smart-fridge concept as an example, Marily walks us through the exact workflow she uses to build products faster: doing user research with Reddit debates, generating PRDs with custom GPTs, prototyping with v0, and even creating stakeholder-ready video mockups using VEO and Sora. She shows how “tool hopping” between specialized AI applications creates a powerful workflow that transforms traditional PM processes and enables more compelling product storytelling. What you’ll learn: How to use Perplexity’s “discussions and opinions” filter to mine Reddit for user insights and create pro/con agent debates that reveal product-market fit requirementsA workflow for transforming market research into comprehensive PRDs using custom GPTs that maintain your personal voice and styleTechniques for turning PRDs into interactive prototypes using v0.dev that make your product vision tangible for stakeholdersHow to create persuasive product videos using Flow and Sora that communicate your vision more effectively than traditional presentationsWhy “tool hopping” between specialized AI applications creates a more powerful workflow than using a single toolHow to use NotebookLM as an interactive judge for product demos and pitch competitions— Brought to you by: WorkOS—Make your app enterprise-ready today Miro—The AI Innovation Workspace where teams discover, plan, and ship breakthrough products — Where to find Marily Nika: LinkedIn: https://www.linkedin.com/in/marilynika/ Website: https://www.marilynika.me/ Substack: https://marily.substack.com/ AI Product Management Bootcamp & Certification by AI Product Academy: https://bit.ly/4p8tn2r — 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 Marily Nika (02:54) Smart-fridge use case inspiration (06:15) Using Perplexity to mine Reddit for user research (11:19) Creating a comprehensive PRD with ChatGPT (13:40) Building an interactive prototype with v0 (16:20) Using prototypes as stakeholder influence tools in product reviews (21:30) Generating product videos with Flow and Sora (30:17) The complete 20-minute product workflow, from research to video (32:06) Using NotebookLM as an AI judge for product demo days (37:38) What to do when AI tools aren’t giving you what you want — Tools referenced: • Perplexity: https://www.perplexity.ai/ • ChatGPT: https://chat.openai.com/ • v0.dev: https://v0.dev/ • Flow (Google Labs): https://labs.google/flow/about • Sora: https://openai.com/sora • NotebookLM: https://notebooklm.google/ — Other references: • AI Product Management Bootcamp: https://maven.com/lenny/ai-product-management • Lenny’s List on Maven: https://maven.com/lenny — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    40 мин.
  6. How to create your own AI performance coach: Optimizing your unique nutrition, recovery, and injury management needs | Lucas Werthein (Cactus)

    24 НОЯБ.

    How to create your own AI performance coach: Optimizing your unique nutrition, recovery, and injury management needs | Lucas Werthein (Cactus)

    Lucas Werthein, the COO and co-founder of Cactus, shares how he built a personalized AI wellness coach using ChatGPT to optimize his athletic performance while managing past injuries. After multiple surgeries on his knees, shoulder, and foot, Lucas created a system that synthesizes data from medical imaging, blood tests, wearable devices, and nutrition plans to provide personalized recommendations. His AI coach helps him balance competitive tennis, weightlifting, and running a company while maintaining his goal of “feeling 25 in a 40-year-old body.” Lucas demonstrates how this approach transforms siloed health information into actionable insights that protect joints, optimize recovery, and extend peak performance. What you’ll learn: How to configure a ChatGPT with multiple data types, including MRIs, x-rays, blood tests, and wearable metrics, to create a comprehensive health profileA framework for setting clear performance boundaries that prioritize joint protection, energy optimization, and injury preventionTechniques for using AI to balance nutrition around special events like social dinners while maintaining performance goalsHow to use images and videos to get AI feedback on physical symptoms and injury recovery timelinesA method for validating and contextualizing medical advice by having AI synthesize information from multiple health-care providersWhy creating clear rules and anti-prompts helps AI deliver practical, evidence-based recommendations instead of trendy supplements or extreme protocols— Copy Lucas’s Health Coach Prompt: https://www.lennysnewsletter.com/p/how-to-create-your-own-ai-performance-coach — Brought to you by: WorkOS—Make your app enterprise-ready today Google Gemini—Your everyday AI assistant — Where to find Lucas Werthein: Website: https://cactus.is/ — 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 Lucas’s athletic background and injury history (04:55) The challenge of synthesizing siloed health data (06:11) Building a GPT to optimize performance and recovery (09:57) Demonstrating the data types integrated into the AI coach (13:54) Configuring the GPT with clear performance goals and boundaries (16:31) Setting realistic expectations for the AI coach (17:50) Creating nutrition, training, and recovery frameworks (21:47) Establishing hard boundaries and anti-prompts (24:25) Example: Managing nutrition around special events (27:30) Accessibility and affordability of on-demand coaching (28:24) Practical examples and real-life scenarios (29:31) Using AI for injury management and recovery planning (34:19) Validating expert opinions and translating medical advice (37:25) Vision for the future of AI in personal health coaching (43:27) Other AI workflows: synthetic clients and AI co-founders (48:48) Final thoughts on AI reliability and evolution — Tool referenced: • ChatGPT: https://chat.openai.com/ — Other references: • InBody scan: https://inbodyusa.com/ • Whoop: https://www.whoop.com/ — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    52 мин.
  7. “Farm-to-table software”: How I built a Thanksgiving party hub using Lovable for managing invites, dishes, shared recipes, and photos

    19 НОЯБ.

    “Farm-to-table software”: How I built a Thanksgiving party hub using Lovable for managing invites, dishes, shared recipes, and photos

    In today’s pre-Thanksgiving episode, I walk you through how I vibe coded my very own “Thanksgiving party hub” using Lovable—and how I transformed it from AI-generated slop into something warm, personal, and genuinely useful. I show you exactly how I upleveled the typography, visuals, and structure using Google Fonts and Midjourney style references, and then I share one of my favorite real-life AI hacks: how to turn any messy online recipe into a clean, step-by-step, kid-friendly version that’s actually usable while you’re cooking. This is a cozy, practical walkthrough of my real design process—the little tricks I use to make AI-built apps feel handcrafted instead of generic. What you’ll learn: How to build a fully functional Thanksgiving party hub in Lovable—guests, dishes, recipes, and photosHow I uplevel AI-generated designs using Google Fonts and TailwindHow to use Midjourney style references to create custom images that match your aestheticHow to add custom features to vibe-coded apps, like dietary preferences and allergen tagsHow to iterate on layouts inside Lovable using screenshots and small, targeted promptsHow I use ChatGPT to restructure recipes so the measurements are embedded directly in each stepHow to make recipes kid-friendly and easier to follow using a simple formatting prompt— Brought to you by: WorkOS—Make your app enterprise-ready today — 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 the Thanksgiving party hub concept (02:20) Starting a project in Lovable and initial design assessment (04:59) Upleveling typography with Google Font combinations (08:36) Creating custom header images with Midjourney (11:39) Adjusting aspect ratios for Midjourney images (14:22) Fixing design issues incrementally (18:52) Adding dietary-restriction functionality (23:36) AI recipe reformatting for easier cooking (26:02) Thoughts on ChatGPT 5.1 (30:51) Final implementation and recipe sharing — Tools referenced: • Lovable: https://lovable.dev/ • Midjourney: https://www.midjourney.com/ • Google Fonts: https://fonts.google.com/ • ChatGPT: https://chat.openai.com/ • Canva Font Combinations: https://www.canva.com/font-combinations/ — Other references: • Polenta and Sausage Stuffing Recipe: https://www.epicurious.com/recipes/food/views/polenta-and-sausage-stuffing-233030 • Runaway Pancakes (kid-friendly recipe site): https://runawaypancakes.com/ — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    34 мин.
  8. “Nobody wanted to do this work”: How Emmy Award–winning filmmakers use AI to automate the tedious parts of documentaries

    17 НОЯБ.

    “Nobody wanted to do this work”: How Emmy Award–winning filmmakers use AI to automate the tedious parts of documentaries

    Tim McAleer is a producer at Ken Burns’s Florentine Films who is responsible for the technology and processes that power their documentary production. Rather than using AI to generate creative content, Tim has built custom AI-powered tools that automate the most tedious parts of documentary filmmaking: organizing and extracting metadata from tens of thousands of archival images, videos, and audio files. In this episode, Tim demonstrates how he’s transformed post-production workflows using AI to make vast archives of historical material actually usable and searchable. What you’ll learn: How Tim built an AI system that automatically extracts and embeds metadata into archival images and footageThe custom iOS app he created that transforms chaotic archival research into structured, searchable dataHow AI-powered OCR is making previously illegible historical documents accessibleWhy Tim uses different AI models for different tasks (Claude for coding, OpenAI for images, Whisper for audio)How vector embeddings enable semantic search across massive documentary archivesA practical approach to building custom AI tools that solve specific workflow problemsWhy AI is most valuable for automating tedious tasks rather than replacing creative work— Brought to you by: Brex—The intelligent finance platform built for founders — Where to find Tim McAleer: Website: https://timmcaleer.com/ LinkedIn: https://www.linkedin.com/in/timmcaleer/ — 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 Tim McAleer (02:23) The scale of media management in documentary filmmaking (04:16) Building a database system for archival assets (06:02) Early experiments with AI image description (08:59) Adding metadata extraction to improve accuracy (12:54) Scaling from single scripts to a complete REST API (15:16) Processing video with frame sampling and audio transcription (19:10) Implementing vector embeddings for semantic search (21:22) How AI frees up researchers to focus on content discovery (24:21) Demo of “Flip Flop” iOS app for field research (29:33) How structured file naming improves workflow efficiency (32:20) “OCR Party” app for processing historical documents (34:56) The versatility of different app form factors for specific workflows (40:34) Learning approach and parallels with creative software (42:00) Perspectives on AI in the film industry (44:05) Prompting techniques and troubleshooting AI workflows — Tools referenced: • Claude: https://claude.ai/ • ChatGPT: https://chat.openai.com/ • OpenAI Vision API: https://platform.openai.com/docs/guides/vision • Whisper: https://github.com/openai/whisper • Cursor: https://cursor.sh/ • Superwhisper: https://superwhisper.com/ • CLIP: https://github.com/openai/CLIP • Gemini: https://deepmind.google/technologies/gemini/ — Other references: • Florentine Films: https://www.florentinefilms.com/ • Ken Burns: https://www.pbs.org/kenburns/ • Muhammad Ali documentary: https://www.pbs.org/kenburns/muhammad-ali/ • The American Revolution series: https://www.pbs.org/kenburns/the-american-revolution/ • Archival Producers Alliance: https://www.archivalproducersalliance.com/genai-guidelines • Exif metadata standard: https://en.wikipedia.org/wiki/Exif • Library of Congress: https://www.loc.gov/ — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    48 мин.
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How I AI, hosted by Claire Vo, is for anyone wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will share a specific, practical, and impactful way they’ve learned to use AI in their work or life. Expect 30-minute episodes, live screen sharing, and tips/tricks/workflows you can copy immediately. If you want to demystify AI and learn the skills you need to thrive in this new world, this podcast is for you.

Информация

  • Автор
    Claire Vo
  • Годы выхода
    2 тыс.
  • Выпуски
    43
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © Claire Vo
  • Сайт подкаста
    How I AI

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