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. Claude Opus 4.6 vs. GPT-5.3 Codex: How I shipped 93,000 lines of code in 5 days

    1日前

    Claude Opus 4.6 vs. GPT-5.3 Codex: How I shipped 93,000 lines of code in 5 days

    I put the newest AI coding models from OpenAI and Anthropic head-to-head, testing them on real engineering work I’m actually doing. I compare GPT-5.3 Codex with Opus 4.6 (and Opus 4.6 Fast) by asking them to redesign my marketing website and refactor some genuinely gnarly components. Through side-by-side experiments, I break down where each model shines—creative development versus code review—and share how I’m thinking about combining them to build a more effective AI engineering stack. — What you’ll learn: The strengths and weaknesses of OpenAI’s Codex vs. Anthropic’s Opus for different coding tasksHow I shipped 44 PRs containing 98 commits across 1,088 files in just five days using these modelsWhy Codex excels at code review but struggles with creative, greenfield workThe surprising way Opus and Codex complement each other in a real-world engineering workflowHow to use Git concepts like work trees to maximize productivity with AI coding assistantsWhy Opus 4.6 Fast might be worth the 6x price increase (but be careful with your token budget)— Brought to you by: WorkOS—Make your app enterprise-ready today — In this episode, we cover: (00:00) Introduction to new AI coding models (02:13) My test methodology for comparing models (03:30) Codex’s unique features: Git primitives, skills, and automations (09:05) Testing GPT-5.2 Codex on a website redesign task (10:40) Challenges with Codex’s literal interpretation of prompts (15:00) Comparing the before and after with Codex (16:23) Testing Opus 4.6 on the same website redesign task (20:56) Comparing the visual results of both models (21:30) Real-world engineering impact: 44 PRs in five days (23:03) Refactoring components with Opus 4.6 (24:30) Using Codex for code review and architectural analysis (26:55) Cost considerations for Opus 4.6 Fast (28:52) Conclusion — Tools referenced: • OpenAI’s GPT-5.3 Codex: https://openai.com/index/introducing-gpt-5-3-codex/ • Anthropic’s Claude Opus 4.6: https://www.anthropic.com/news/claude-opus-4-6 • Cursor: https://cursor.sh/ • GitHub: https://github.com/ — Other references: • Tailwind CSS: https://tailwindcss.com/ • Git: https://git-scm.com/ • Bugbot: https://cursor.com/bugbot — 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.

    30分
  2. How to build your own AI developer tools with Claude Code | CJ Hess (Tenex)

    3日前

    How to build your own AI developer tools with Claude Code | CJ Hess (Tenex)

    CJ Hess is a software engineer at Tenex who has built some of the most useful tools and workflows for being a “real AI engineer.” In this episode, CJ demonstrates his custom-built tool, Flowy, that transforms Claude’s ASCII diagrams into interactive visual mockups and flowcharts. He also shares his process for using model-to-model comparison to ensure that his AI-generated code is high-quality, and why he believes we’re just at the beginning of a revolution in how developers interact with AI. What you’ll learn: How CJ built Flowy, a custom visual planning tool that converts JSON files into interactive mockups and flowchartsWhy visual planning tools are more effective than ASCII diagrams for complex UI and animation workflowsHow to create and use Claude Code skills to extend your development environmentUsing model-to-model comparison (Claude + Codex) to improve code qualityHow to build your own ecosystem of tools around Claude CodeThe value of bypassing permissions in controlled environments to speed up development— Brought to you by: Orkes—The enterprise platform for reliable applications and agentic workflows Rovo—AI that knows your business — Detailed workflow walkthroughs from this episode: • How I AI: CJ Hess on Building Custom Dev Tools and Model-vs-Model Code Reviews: https://www.chatprd.ai/how-i-ai/cj-hess-tenex-custom-dev-tools-and-model-vs-model-code-reviews • Implement Model-vs-Model AI Code Reviews for Quality Control: https://www.chatprd.ai/how-i-ai/workflows/implement-model-vs-model-ai-code-reviews-for-quality-control • Develop Features with AI Using Custom Visual Planning Tools: https://www.chatprd.ai/how-i-ai/workflows/develop-features-with-ai-using-custom-visual-planning-tools — In this episode, we cover: (00:00) Introduction to CJ Hess (02:48) Why CJ prefers Claude Code for development (04:46) The evolution of developer environments with AI (06:50) Planning workflows and the limitations of ASCII diagrams (08:23) Introduction to Flowy, CJ’s custom visualization tool (11:54) How Flowy compares to mermaid diagrams (15:25) Demo: Using Flowy (19:30) Examining Flowy’s skill structure (23:27) Reviewing the generated flowcharts and diagrams (28:34) The cognitive benefits of visual planning vs. text-based planning (31:38) Generating UI mockups with Flowy (33:30) Building the feature directly from flowcharts and mockups (35:40) Quick recap (36:51) Using model-to-model review with Codex (Carl) (41:52) The benefits of using AI for code review (45:13) Lightning round and final thoughts — Tools referenced: • Claude Code: https://claude.ai/code • Claude Opus 4.5: https://www.anthropic.com/news/claude-opus-4-5 • Cursor: https://cursor.sh/ • Obsidian: https://obsidian.md/ • GPT-5.2 Codex: https://openai.com/index/introducing-gpt-5-2-codex/ • Google’s Project Genie: https://labs.google/projectgenie — Other references: • Mermaid diagrams: https://mermaid.js.org/ • Figma: https://www.figma.com/ • Excalidraw: https://excalidraw.com/ • TypeScript: https://www.typescriptlang.org/ — Where to find CJ Hess: LinkedIn: https://www.linkedin.com/in/cj-hess-connexwork/ X: https://x.com/seejayhess — 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.

    53分
  3. Guillermo Rauch: Vercel CEO on how v0 hit 3,200 PRs merged per day (and lets anyone ship)

    2月4日

    Guillermo Rauch: Vercel CEO on how v0 hit 3,200 PRs merged per day (and lets anyone ship)

    Guillermo Rauch, the CEO of Vercel, demonstrates how v0 has evolved from a simple prototyping tool to a complete development environment that supports the entire Git workflow. Guillermo shows how Vercel built skills.sh—a viral marketplace with over 34,000 community-submitted skills—using v0, and how the tool enables non-technical team members to contribute production-ready code changes. He walks through creating branches, implementing features, previewing changes, and submitting pull requests, all within v0. What you’ll learn: How v0’s new Git workflow integration enables anyone to contribute production-ready code changesWhy skills.sh became a viral hub for AI skills, with 500 new submissions per hourHow to implement features in v0 that consider production concerns like abuse prevention and rate limitingThe benefits of branch previews for testing changes in a production-like environment before mergingHow v0 eliminates development environment setup challenges for non-technical team membersWhy the “terminal core” design aesthetic became central to skills.sh’s interfaceHow Vercel uses v0 internally to democratize code contributions across teamsThe future of AI at Vercel, including upcoming tools for text-to-SVG and video generation— In this episode, we cover: (00:00) Introduction (01:22) Overview of skills.sh (04:40) Demonstration of v0’s GitHub integration and branch creation (06:40) Exploring the v0 development environment (09:05)  Building a rating system feature for skills.sh (11:18) Testing the new feature in the preview environment (13:20) Creating a pull request and deploying to a preview environment (15:25) How Vercel is using v0 internally for production work (17:48) Organizational adoption and cultural impact (22:04) Favorite non-coding AI use cases (25:17) AI-powered chess game built with v0 (27:57) Teaching kids about coding with AI (31:44) Troubleshooting techniques when AI gets stuck (34:43) Final thoughts and audience Q&A — Tools referenced: • v0: https://v0.dev/ • Skills by Vercel: https://skills.sh/vercel • Vercel: https://vercel.com/ • GitHub: https://github.com/ • Nano Banana: https://gemini.google/overview/image-generation/ • Vestaboard: https://vestaboard.com/ — Other references: • v0 Chess Match: https://v0-chess-match.app/ • React Native: https://reactnative.dev/ — Where to find Guillermo Rauch: LinkedIn: linkedin.com/in/rauchg X: https://twitter.com/rauchg — 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.

    44分
  4. How this PM uses MCPs to automate his meeting prep, CRM updates, and customer feedback synthesis | Reid Robinson (Zapier)

    2月2日

    How this PM uses MCPs to automate his meeting prep, CRM updates, and customer feedback synthesis | Reid Robinson (Zapier)

    Reid Robinson, Principal AI Product Strategist at Zapier, shares how he uses Model Context Protocols (MCPs) to automate tedious tasks and create powerful workflows. He demonstrates practical workflows that combine Zapier’s more than 8,000 app connections with AI tools like Claude to create systems that work while he sleeps. What you’ll learn: How to use Zapier’s MCP server to create custom collections of tools that work seamlessly with Claude, ChatGPT, and other AI assistantsA workflow for using Claude Projects to provide detailed instructions for tool usage, improving reliability and consistencyHow to automate CRM updates and meeting preparation by connecting AI to your calendar, notes, and internal knowledge basesA system for creating a virtuous cycle of customer feedback by automatically analyzing support tickets and updating knowledge basesWhy thinking about “what your AI could do while you sleep” is a powerful framework for identifying high-impact automation opportunitiesPersonal use cases, including family calendar management and creating custom songs that demonstrate AI’s ability to bring joy beyond work— Brought to you by: WorkOS—Make your app enterprise-ready today Vanta—Automate compliance and simplify security — In this episode, we cover: (00:00) Introduction to Reid Robinson and his role at Zapier (02:41) Understanding MCPs as app integrations for AI tools (04:05) How Zapier’s approach to MCPs works with over 8,000 apps (09:00) Using Claude Projects to improve tool usage instructions (12:05) Post-meeting notes management (15:25) Comparing deterministic workflows vs. agentic instructions (18:15) Reid’s idea jammer (20:04) Building a customer interview preparation workflow (23:10) Using Gemini for processing file-based data (25:05) Creating a virtuous cycle of customer feedback analysis (29:16) The “if you could run ChatGPT in your sleep” framework (31:48) Quick recap (33:03) Personal use cases (37:16) Using Notebook AI to prepare personalized interview prep — Tools referenced: • Reid’s Resources for How I AI: https://how-i-ai-reid.zapier.app/resources • Claude: https://claude.ai/ • Zapier: https://zapier.com/ • Zapier MCP: https://zapier.com/mcp • Granola: https://www.granola.ai/ • Coda: https://coda.io/ • Suno: https://suno.ai/ • Notebook AI: https://www.notebook.ai/ • Gemini: https://gemini.google.com/ — Other references: • HubSpot: https://www.hubspot.com/ • Databricks: https://www.databricks.com/ — Where to find Reid Robinson: LinkedIn: https://www.linkedin.com/in/reidtrobinson/ — 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.

    40分
  5. I gave Clawdbot (aka Moltbot) access to my computer, calendar, and emails: Here’s what happened

    1月28日

    I gave Clawdbot (aka Moltbot) access to my computer, calendar, and emails: Here’s what happened

    In this episode, I take you through my unfiltered experience with Clawdbot, the viral open-source AI agent that’s been taking over tech Twitter. (In the time since this was recorded, the tool was renamed Moltbot, but we’re calling it Clawdbot here to match the episode.) It’s an autonomous AI that can run code, spin up sub-agents, join video calls, and take real actions on your machine. I invite it onto the podcast, give it screen access, and walk through what it’s like to go from zero to one with an agentic AI that actually does things. Along the way, I share the real experience: installation headaches, dependency chaos, security warnings you shouldn’t ignore, and the very real tension of giving an AI access to your messaging apps, files, and accounts. I also break down how I thought about permissions, identity, model choice, and cost while testing Clawdbot as a personal assistant. — What you’ll learn: How to install and set up Clawdbot (and why it’s not as simple as the “one-liner” suggests)The security implications of giving an autonomous AI access to your computer and accountsHow to safely limit Clawdbot’s permissions while still making it usefulWhy Clawdbot struggles with basic time concepts but excels at research tasksThe future of AI assistants—and who might build the consumer-friendly versionHow to use voice messaging with AI agents for on-the-go productivityWhy latency is one of the biggest challenges for autonomous AI assistants— Brought to you by: Lovable—Build apps by simply chatting with AI — Detailed workflow walkthroughs from this episode: • How I AI: My 24 Hours with Clawdbot (aka Moltbot)—3 Workflows for a Powerful (and Terrifying) AI Agent: https://www.chatprd.ai/how-i-ai/24-hours-with-clawdbot-moltbot-3-workflows-for-ai-agent • How to Securely Set Up and Configure an Open-Source AI Agent like Clawdbot: https://www.chatprd.ai/how-i-ai/workflows/how-to-securely-set-up-and-configure-an-open-source-ai-agent-like-clawdbot • How to Safely Delegate Calendar Scheduling to an AI Agent: https://www.chatprd.ai/how-i-ai/workflows/how-to-safely-delegate-calendar-scheduling-to-an-ai-agent • Automate Market Research on Reddit Using an AI Agent: https://www.chatprd.ai/how-i-ai/workflows/automate-market-research-on-reddit-using-an-ai-agent — In this episode, we cover: (00:00) Introduction and getting Clawdbot to join the podcast (02:07) What Clawdbot is and how it works (03:50) Installation process and hardware requirements (07:26) Security considerations and creating separate accounts (08:03) Setting up Telegram integration (10:02) Use case: Clawdbot as an EA (13:08) Configuring the AI agent  (14:31) Granting Google Calendar access (18:03) Testing Clawdbot as a personal assistant (23:16) Speed frustrations (23:54) Email mishaps and impersonation issues (26:33) Why prompting matters more than ever with autonomous agents (27:32) Quick recap and family calendar management gone wrong (32:11) Using voice messaging with Clawdbot (36:14) Product thoughts (37:06) Building a Next.js app to show chat history (42:29) Research capabilities and Reddit analysis (46:10) Final thoughts on security concerns (48:00) The future of AI assistants and who will build them — Tools referenced: • Moltbot (formerly Clawdbot): https://www.molt.bot/ • Telegram: https://telegram.org/ • Vercel: https://vercel.com/ • Devin: https://www.devin.ai/ — Other references: • 1Password: https://1password.com/ • Next.js: https://nextjs.org/ • Google Workspace: https://workspace.google.com/ • Claude Sonnet 4.5: https://www.anthropic.com/news/claude-sonnet-4-5 • OAuth: https://oauth.net/ — 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.

    56分
  6. Advanced Claude Code techniques: context loading, mermaid diagrams, stop hooks, and more | John Lindquist

    1月26日

    Advanced Claude Code techniques: context loading, mermaid diagrams, stop hooks, and more | John Lindquist

    John Lindquist is the co-founder of egghead.io and an expert in leveraging AI tools for professional software development. In this episode, John shares advanced techniques for using AI coding tools like Claude Code and Cursor that go far beyond basic prompting. He demonstrates how senior engineers can use mermaid diagrams for context loading, create custom hooks for automated code quality checks, and build efficient command-line tools that streamline AI workflows. What you’ll learn: How to use mermaid diagrams to preload context into Claude Code for faster, more accurate coding assistanceCreating custom hooks in Claude Code to automatically check for TypeScript errors and commit working codeBuilding efficient command-line aliases and tools to streamline your AI workflowsTechniques for using AI to generate documentation that works for both humans and machinesHow to leverage AI for code investigation and orientation when tackling unfamiliar codebasesStrategies for resetting AI conversations when they go off track— Brought to you by: WorkOS—Make your app enterprise-ready today Tines—Start building intelligent workflows today — In this episode, we cover: (00:00) Introduction to John Lindquist (03:15) Using context and diagrams to provide context to AI tools (05:38) Demo: Mermaid diagrams (06:48) Preloading context with system prompts in Claude Code (10:30) The rise of specialized file formats for AI consumption (13:23) Mermaid diagram use cases (19:01) Demo: Creating aliases for common AI commands (21:05) Building custom command-line tools for AI workflows (26:39) Demo: Setting up stop hooks for automated code quality checks (35:16) Investing in quality outputs (36:40) Additional use cases for hooks beyond code quality (39:19) Quick review (41:14) Terminal UI vs. IDE (45:35) Selling AI to skeptical teams (51:57) Prompting reset tricks — Tools referenced: • Claude Code: https://claude.ai/ • Cursor: https://cursor.sh/ • Gemini: https://gemini.google.com/ — Other references: • Zsh: https://www.zsh.org/ • GitHub: https://github.com/ • TypeScript: https://www.typescriptlang.org/ • Bun: https://bun.sh/ • Claude hooks: https://code.claude.com/docs/en/hooks — Where to find John Lindquist: Website: https://egghead.io Newsletter: https://egghead.io/newsletters/ai-dev-essentials LinkedIn: linkedin.com/in/john-lindquist-84230766 X: https://x.com/johnlindquist — 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.

    57分
  7. Claude Code for product managers: research, writing, context libraries, custom to-do system, and more | Teresa Torres

    1月19日

    Claude Code for product managers: research, writing, context libraries, custom to-do system, and more | Teresa Torres

    Teresa Torres is the author of Continuous Discovery Habits and an internationally acclaimed speaker and coach. In this episode, Teresa demonstrates how she’s built a personalized productivity system using Claude Code to manage her tasks, automate research collection, and improve her writing. She shows how non-developers can leverage AI tools to create personalized workflows that match their unique needs and thinking style. What you’ll learn: How Teresa built a personalized task management system in Claude Code that matches her exact workflow needsWhy she moved from Trello to a markdown-based system that gives her complete control and searchabilityHow she automated academic research collection with daily digests of relevant papersHer strategy for organizing context files to make Claude more effective without overwhelming itWhy “pair programming” with Claude has become her approach to everything from writing to task managementHow she uses Claude as a writing partner while maintaining her authentic voiceThe power of slash commands and automation to reduce friction in daily workflows— Brought to you by: Brex—The intelligent finance platform built for founders Graphite—The next generation of code review — In this episode, we cover: (00:00) Introduction to Teresa Torres (02:10) Why Claude Code became Teresa’s productivity tool of choice (03:00) The evolution from browser-based AI to terminal-based workflows (04:14) Demo: Creating a personalized task management system (07:52) How the task system works with markdown files and Obsidian (12:56) Quick recap (14:13) Taking notes within tasks for better searchability (15:54) Demo: Automated research digest workflow (19:32) How the research plugin searches and summarizes academic papers (24:43) Filtering overwhelming information sources (29:00) Using small, focused context files instead of one large document (32:58) Claude as a writing partner: review, research, and refinement (35:34) Recap of workflows and lightning round — Tools referenced: • Claude Code: https://claude.ai/ • Obsidian: https://Obsidian.md/ • VS Code: https://code.visualstudio.com/ • Descript: https://www.descript.com/ • ChatGPT: https://chat.openai.com/ • Trello: https://trello.com/ — Other references: • Continuous Discovery Habits: https://www.producttalk.org/continuous-discovery-habits/ • Google Scholar: https://scholar.google.com/ • Claude Code: What It Is, How It’s Different, and Why Non-Technical People Should Use It: https://www.producttalk.org/claude-code-what-it-is-and-how-its-different — Where to find Teresa Torres: Blog: https://producttalk.org/ Podcast: https://justnowpossible.com/ Book: https://www.amazon.com/Continuous-Discovery-Habits-Discover-Products/dp/1736633309 LinkedIn: https://www.linkedin.com/in/teresatorres/ — 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.

    43分
  8. The power user’s guide to Codex: parallelizing workflows, planning techniques, advanced context engineering tips, automating code reviews, and more | Alexander Embiricos

    1月12日

    The power user’s guide to Codex: parallelizing workflows, planning techniques, advanced context engineering tips, automating code reviews, and more | Alexander Embiricos

    Alexander Embiricos, the product lead for Codex at OpenAI, shares practical workflows for getting the most out of this AI coding agent. In this episode, he demonstrates how both non-technical users and experienced engineers can leverage Codex to accelerate development, from making simple code changes to building production-ready applications. Alex walks through real examples of using Codex in VS Code and terminal environments, implementing parallel workflows with Git worktrees, and creating detailed implementation plans for complex projects. He also reveals how OpenAI uses Codex internally, including how they built the Sora Android app in just 28 days, and offers insights on automated code review and the future of AI-assisted development. What you’ll learn: How to set up and use Codex in VS Code and terminal environments for both simple and complex coding tasksA practical workflow for running multiple Codex instances in parallel using Git worktrees to avoid conflictsHow to create detailed implementation plans using the Plans.md technique for complex engineering projectsWhy context is critical when prompting Codex—and how to provide the right information for better resultsHow OpenAI uses automated code review to accelerate development while maintaining high quality standardsThe key differences between vibe coding for prototypes versus building production-ready applications with AIHow the new GPT-5.2 model improves Codex’s capabilities with faster reasoning and better problem-solving— Brought to you by: Brex—The intelligent finance platform built for founders Graphite—Your AI code review platform — Detailed workflow walkthrough from this episode: https://chatprd.ai/how-i-ai/advanced-codex-workflows-with-openai-alex-embiricos — In this episode, we cover: (00:00) Introduction to Alex and Codex (02:06) Getting started with Codex (04:54) Using Codex for parallel tasks (07:34) Understanding Git worktrees (09:51) Terminal shortcuts and command-line efficiency (12:16) How OpenAI built the Sora Android app with Codex (15:37) Using PLANS.md for problem solving (17:57) The importance of high agency (22:22) Deciding between what needs a plan and what doesn’t (26:42) How to multiply the impact of Codex (28:08) Implementing automated code review with GitHub (31:58) Delivering the benefits of AGI to all humanity (34:35) Accelerating developer productivity (36:38) Recap and final thoughts — Tools referenced: • Codex: https://openai.com/blog/openai-codex • VS Code: https://code.visualstudio.com/ • Cursor: https://cursor.com/ • Git: https://git-scm.com/ • GitHub: https://github.com/ • Atlas: https://openai.com/atlas • ChatGPT: https://chat.openai.com/ • Slack: https://slack.com/ • Linear: https://linear.app/ — Other references: • Sora Android app: https://openai.com/blog/sora • GPT-5.2 model: https://openai.com/index/introducing-gpt-5-2/ • SWE-bench: https://openai.com/index/introducing-swe-bench-verified/ — Where to find Alexander Embiricos: LinkedIn: https://www.linkedin.com/in/embirico X: https://x.com/embirico — 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.

    53分
すべて見る（53）

予告編

番組について

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.

情報

  • クリエイター
    Claire Vo
  • 配信期間
    25年 - 26年
  • エピソード
    53
  • 制限指定
    不適切な内容を含まない
  • Copyright
    © Claire Vo
  • 番組のWebサイト
    How I AI

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