How I AI

Claire Vo

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. 8 uur geleden

    From zero coding background to hardware hacker: How Cursor + a Raspberry Pi makes AI fun

    Maddie Reese is a vibe coder, hardware tinkerer, and builder. She builds things at the intersection of software and hardware, including a thermal receipt printer that people around the world can message directly, a fully functional Twitter pager running on a Raspberry Pi, and a personal API that tells you her coffee order so you don’t have to ask. Maddie approaches hardware the same way she approaches software: dump the idea into Cursor, let it interview her, get a shopping list, triple-check the parts before buying, and build. She got her start after her dad introduced her to Lovable, and she locked herself in her room and didn’t come up for air. What you’ll learn: How Maddie built a thermal receipt printer that accepts messages from anywhere in the world using a Raspberry Pi and BluetoothHow to use Cursor’s agent view to brainstorm a hardware projectWhat belongs in a personal API and why agents, not just humans, will be the ones using itHow to read just enough code to do some damage, without needing to understand all of itWhy building for fun, not practicality, is the fastest path to actually shipping physical projects— Brought to you by: Firecrawl—Power AI agents with clean web data Customer.io—Build customer engagement campaigns from a single prompt — In this episode, we cover: (00:00) Intro (02:00) Maddie’s AI pill moment (03:53) The thermal receipt printer: live demo and how it works (11:10) The pager project (17:23) Why she uses Cursor’s clean agent view instead of terminals and browsers (19:05) The personal API: coffee order, pets, favorite snacks, and more (22:57) Lightning round and final thoughts — Tools referenced: • Cursor: https://www.cursor.com/ • Lovable: https://lovable.dev/ • Raspberry Pi: https://www.raspberrypi.com/ • Resend: https://resend.com/ • Cloudflare Workers: https://workers.cloudflare.com/ • Supabase (Conduct database referenced): https://supabase.com/ • Twitter/X API: https://developer.x.com/ • Spoke pager network: https://www.spoke.com/ • OpenClaw: https://openclaw.ai/ — Where to find Maddie Reese: Website: https://maddiedreese.com Message her directly: https://maddiedreese.com/message X: https://x.com/maddiedreese — 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.

    From zero coding background to hardware hacker: How Cursor + a Raspberry Pi makes AI fun

  2. 3 dgn geleden

    Claude Opus 5 review: this model is brilliant (but annoying)

    I’m tired of new models. Every week there’s a new benchmark, a new frontier intelligence claim, a new thing to test. But here we are, because Opus 5 just dropped and I’ve had real hands-on time with it, so you’re getting the honest version. This is my full Opus 5 review: personality analysis, live benchmark results from my 7-model How I AI eval, and an actual verdict on whether I’m swapping it in. Spoiler: the answer surprised me. What you’ll learn: Why I think we’ve hit an intelligence overhang and what that means for which model variables actually matter nowHow Opus 5’s “neurotic” personality showed up in real coding sessions, including a merge conflict it refused to touchWhat I learned from asking both Opus 5 and GPT‑5.6 Sol “who’s smarter, you or me?”Where Opus 5, GPT‑5.6 Sol, Sonnet 5, and Gemini 3.1 Pro actually landed on the HIA benchmark leaderboardThe one use case where Opus 5 earned straight 5s from meMy actual plan for using Opus 5 going forward— In this episode, I cover: (00:00) Opus 5 is here (03:15) First impressions (06:12) Opus 5 vs. GPT‑5.6 Sol personality comparison (14:39) Claude Slop: the verbosity problem and why it makes my blood boil (16:55) How the How I AI benchmark works (7 models, 6 tasks, blind scoring) (18:30) Live benchmark results: the leaderboard reveal (23:25) My verdict and how I’ll actually use Opus 5 — Tools referenced: • Claude Opus 5: • Anthropic blog: https://www.anthropic.com/news • GPT‑5.6 Sol: https://openai.com/index/previewing-gpt-5-6-sol/ • Sonnet 5: https://www.anthropic.com/news/claude-sonnet-5 • Gemini 3.1 Pro: https://deepmind.google/models/gemini/pro/ — 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.

    Claude Opus 5 review: this model is brilliant (but annoying)

  3. 5 dgn geleden

    Computer & browser use in Codex (5 real examples)

    Today I’m walking you through one of my absolute favorite AI features right now: browser and computer use via Codex (the ChatGPT desktop app). I use this every single day, personally and professionally, and I wanted to share the specific workflows I’ve built, the moments that surprised me, and the mental model that makes it actually click. What you’ll learn: How browser use and computer use work, and why the Codex desktop app plus Chrome extension is the combo I rely onHow I use Codex to QA my onboarding flow, including exhaustive mobile testing I would never do manuallyWhy under-prompting frontier models gets better results than detailed step-by-step instructionsHow my husband EJ Lawless’s persona-impersonation trick surfaces friction points I can’t see as the builderHow I use browser use to get through my LinkedIn inbox without touching it myselfHow I had Codex shop Free People’s sale and add 10 medium items to my cart (breastfeeding-friendly and Hawaii-ready)How computer use can control iPhone mirroring so your Mac can technically operate your phoneThree more computer-use shortcuts: filling annoying forms, creating Google Sheets mid-workflow, and managing router— Brought to you by: Runway—The creative AI platform for images, video and more Hyperagent—Deploy fleets of agents that handle real work — In this episode, we cover: (00:00) Intro (01:46) What browser use and computer use actually are (03:08) Why I use Codex specifically and how the desktop app plus Chrome extension works (04:15) Use case 1: QA testing my onboarding flow (10:41) Results: 11 issues, one high-severity blocker, one Google Sheet with screenshots (12:10) Use case 2: persona testing (18:20) Use case 3: LinkedIn inbox, hands-free (20:37) Use case 4: AI personal shopper (23:47) Rapid-fire uses: forms, iPhone mirroring, router access from out of state, Google Docs (26:50) Wrap-up — Tools referenced: • Codex (ChatGPT desktop app): https://openai.com/codex • Claude desktop app: https://claude.ai/download • Monologue (voice dictation for AI): https://monologue.app • iPhone mirroring (Apple): https://support.apple.com/en-us/111775 • Google Sheets: https://sheets.google.com — Other references: • Jesse Genet episode (How I AI): https://www.lennysnewsletter.com/p/5-openclaw-agents-run-my-home-finances?utm_source=publication-search — 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.

    Computer & browser use in Codex (5 real examples)

  4. 20 jul

    How the founder of Morning Brew built a Claude content machine that never runs out of ideas and never sounds like slop | Alex Lieberman

    Alex Lieberman co-founded Morning Brew in college and grew it into one of the most-read business newsletters in the world before selling it to Business Insider. Now he’s the co-founder and co-managing partner of Tenex. In this episode, Alex explains why distribution is becoming a durable moat, why founders and teams need to “climb Cringe Mountain,” and how he rebuilt his content process around AI without letting it produce generic slop. He walks us through every step of his Content Machine live: an Oracle that scans internal systems and the internet for content spikes, an interview panel that pulls out his real ideas, voice and style files that keep drafts sounding like him, an editorial council that scores and revises posts, and a lessons loop that learns from his feedback. What you’ll learn: Why the blank page is the biggest friction point in content creation, and how an AI Oracle eliminates itHow to map your current workflow before you add any AIHow Alex built a six-step Content Machine in Claude that goes from idea spike to publishable postWhy the interview step (not the drafting step) is where AI slop actually comes fromHow to codify your voice in a Markdown file so an AI drafts in your register, not the internet’s averageWhy your employees are your most underleveraged marketing channel right nowHow the Tenex Creator Cup turned content creation into a team sport with a $5,000 prize pool— Brought to you by: Firecrawl—Power AI agents with clean web data Customer.io—Build customer engagement campaigns from a single prompt — In this episode, we cover: (00:00) Introduction to Alex Lieberman (02:35) Why Alex built a content machine (06:56) Alex’s thoughts on AI slop (09:00) Mapping the workflow from scratch (13:24) The six-step Content Machine setup (23:11) Live demo: Oracle, Interview Panel, and Writer’s Council in action (30:38) Employee advocacy: the Tenex Creator Cup and $5K prize pool (36:45) Lightning round: great engineers, AI use cases, slop fixes — Tools referenced: • Claude / Claude Code (Anthropic): https://claude.ai • Wispr Flow (voice-to-text transcription): https://wisprflow.ai • Notion: https://notion.so • Linear: https://linear.app • Slack: https://slack.com — Other references: • Morgan Housel: https://www.morganhousel.com • David Perell: https://perell.com • Shaan Puri / My First Million podcast: https://www.mfmpod.com • Gary Vaynerchuk: https://garyvaynerchuk.com — Where to find Alex Lieberman: X: https://x.com/businessbarista LinkedIn: https://www.linkedin.com/in/alex-lieberman/ Tenex: https://www.tenex.co/ — 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.

    How the founder of Morning Brew built a Claude content machine that never runs out of ideas and never sounds like slop | Alex Lieberman

  5. 13 jul

    This solo builder runs 24/7 local AI on his own hardware | Alex Finn

    Alex Finn is an AI builder, YouTuber, and the creator of Vibe Code Academy, a community for people learning to build with AI tools. He runs one of the most ambitious local AI setups I’ve come across: three Mac Studio 512 GB machines, a DGX Spark, and a custom RTX 5090 build, all coordinated through a fleet dashboard he built himself. He’s spent five months figuring out which local models belong on which machines, how to wire them to Claude Code loops, and how to get a software factory running without babysitting it. What you’ll learn: How Alex chose between a Mac Studio (512 GB unified memory), DGX Spark, and RTX 5090, and what each is actually good forWhy Tailscale is worth installing even on a single machine, and how it lets one agent manage your entire hardware fleetHow the build loop and review loop in Claude Code workHow to allocate tasks by machine and modelWhy unlimited local inference changes the use-case math in a way a $20 cloud subscription never canWhat OpenClaw and Hermes are each best suited for, and why Alex runs five agents total with failover baked in— Brought to you by: Runway—The creative AI platform for images, video, and more Jira Product Discovery—Prioritize with insights, build with confidence — In this episode, we cover: (00:00) Intro (02:58) Alex's hardware stack (03:48) What "ambient AI" means (04:15) Alex's red-pill moment with OpenClaw (07:04) Mac Studio vs. DGX Spark vs. RTX 5090 (13:24) How to set up local models with no technical knowledge (Tailscale + OpenClaw/Hermes) (17:16) Fleet control dashboard: assigning 24/7 tasks across machines (20:42) Local models as security scanners feeding Claude Code (22:25) How Alex allocates GLM 5.2, Qwen 3.6, and Ornith 1.0 by task (24:28) OpenClaw vs. Hermes: the honest comparison (26:55) The software factory: build loop, review loop, rocket emoji (31:55) Lightning round: favorite hardware, favorite model, prompting style (34:46) Where to find Alex — Tools referenced: • Claude Code: https://claude.ai/code • OpenClaw: https://openclaw.ai/ • Hermes: https://hermes-agent.nousresearch.com/ • Tailscale: https://tailscale.com/ • Codex (OpenAI): https://openai.com/codex • GLM 5.2 (z.ai): https://huggingface.co/zai-org/GLM-5.2 • Qwen 3.6 (Alibaba): https://huggingface.co/Qwen/Qwen3.6-35B-A3B • Ornith 1.0: https://github.com/deepreinforce-ai/Ornith-1 • Gemma 4: https://huggingface.co/collections/google/gemma-4 • Playwright (browser testing): https://playwright.dev/ • Vercel (preview deploys): https://vercel.com/ — Other references: • DGX Spark (Nvidia): https://www.nvidia.com/en-us/products/workstations/dgx-spark/ • Mac Studio (Apple): https://www.apple.com/mac-studio/ • How to design AI agent loops: schedules, goals, and subagents in Claude Code and Codex: https://www.lennysnewsletter.com/p/how-to-design-ai-agent-loops-schedules — Where to find Alex Finn: LinkedIn: https://www.linkedin.com/in/alex-finn-1848684a YouTube: https://www.youtube.com/@AlexFinnOfficial X: https://x.com/AlexFinn — 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.

    This solo builder runs 24/7 local AI on his own hardware | Alex Finn

  6. 9 jul

    GPT-5.6 Sol vs. Claude Fable: Why OpenAI’s new model crushes my benchmark

    GPT-5.6 Sol is back, and I ran it through my full How I AI vibe benchmark against GPT-5.6 Terra, Luna, Claude Fable 5, and Sonnet 5 across five categories: PRDs, prototypes, wireframes, debugging, and agentic voice. Sol won by a meaningful margin on my Claire Weighted Index (70% my taste, 30% Terminal Bench 2.1), and I also tested two use cases I can't stop thinking about: building a gamified homework tracking app for my kids in one shot with Codex, and browser automation with Chrome that burned through 500 LinkedIn replies while I did literally nothing. What you’ll learn: How I scored five AI models (including GPT 5.6 Sol, Fable 5, and Sonnet 5) using my “Claire Weighted Index” benchmark across PRDs, prototypes, code, and agentic voiceThe difference between GPT-5.6 Sol (Terra) and Sol for PRD writingHow Fable’s precision and pedantry made it harder to collaborate with, and the exact moment Sol broke through where Fable got stuckWhy Sonnet 5 is still my go-to for agentic voice in OpenClaw, even after this whole benchmarkHow I used GPT-5.6 Sol in Codex to build a fully gamified homework tracking app for my kids in one shotThe video editing use case that saved me hours clipping a talk I gave at Cursor’s eventHow to use Codex plus GPT-5.6 and Chrome for browser automation, and why this is my single most-loved use case right now— In this episode, I cover: (00:00) Intro (01:10) The three GPT-5.6 models: Sol, Terra, Luna (02:17) Pricing: Sol vs. Fable API costs (03:24) The How I AI benchmark (05:03) Claire-weighted Index results (07:00) Per-task winners: prototypes, PRDs, agentic voice (11:59) What Claire actually rewards (13:20) Full-fidelity prototype side-by-sides (Sol vs. Fable) (17:45) Wireframes (18:19) Agentic voice (19:15) Where Sol is better than other models (23:56) Gamified kids’ homework app, built in one shot (28:02) Fable’s pedantry problem and how Sol broke through it (31:49) Two bonus use cases: video editing and browser use (35:08) Final summary and model recommendations — Tools referenced: • GPT 5.6 (Sol, Terra, Luna): https://help.openai.com/en/articles/20001325-a-preview-of-gpt-56-sol-terra-and-luna • Codex: https://openai.com/codex • ChatPRD: https://www.chatprd.ai/ • CapCut: https://www.capcut.com/ • Math Academy: https://www.mathacademy.com/ — Other references: • Cursor event where Claire spoke on the future of PM: https://www.youtube.com/watch?v=4CAFK-rc26A • ChatPRD blog (where benchmark outputs will be published): https://www.chatprd.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 — Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email jordan@penname.co.

    GPT-5.6 Sol vs. Claude Fable: Why OpenAI’s new model crushes my benchmark

  7. 8 jul

    What a harness is and how to build one with Claude Agent SDK

    Everybody is saying, “It’s not the model, it’s the harness,” but almost nobody stops to explain what a harness actually is. So I did. I built one live on the show: a Sentry bug-debugging harness for my company ChatPRD, using the Claude Agent SDK, a custom terminal UI built with the Ink library, and opinionated adapters for Sentry, Linear, GitHub, and Vercel. The harness handles evidence gathering, root-cause analysis, and follow-up artifact creation, all without me needing to type “dear agent, please fix this bug” ever again. I also walk through the architecture, share the code structure, and give you the exact process I used so you can build your own harness for any repetitive, structured workflow in your business. What you’ll learn: What a harness actually isWhen to build a harness versus when to stick with a general-purpose tool like Claude Code or CodexHow to encode specific permissions into a harnessThe three components every harness needsHow I used GPT-5.5 and Claude Opus to build the harness code itself (and where they both initially resisted)How to structure the artifacts your harness produces so the whole team can use the output— Brought to you by: Bolt.new—Turn your idea into a real product Customer.io—Build customer engagement campaigns from a single prompt — In this episode, we cover: (00:00) What is an AI harness? (03:19) When to build a harness (04:33) Why Claire picked bug triage (06:00) Why not just use Claude Code? (07:48) Demo: The custom harness interface (11:04) Architecture: runs, tasks, tools, and artifacts (13:44) Building it with Codex and Claude (15:08) Code map and file layout (16:51) A look at the code (19:18) The live investigation result (21:01) How to build your own harness — Tools referenced: • Claude Agent SDK (Anthropic): https://code.claude.com/docs/en/agent-sdk/overview • Claude Sonnet 4.6 (model used inside the harness): https://www.anthropic.com/news/claude-sonnet-4-6 • Claude Opus (used to build the harness): https://www.anthropic.com/claude/opus • GPT-5.5 (Codex, used to build the harness): https://openai.com/index/introducing-gpt-5-5/ • Ink (terminal UI library for Node.js): https://github.com/vadimdemedes/ink • Sentry (error monitoring): https://sentry.io/ • Linear (project management): https://linear.app/ • GitHub: https://github.com/ • Vercel: https://vercel.com/ — 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.

    What a harness is and how to build one with Claude Agent SDK

  8. 6 jul

    How I run autonomous coding agents from my phone with OpenAI Symphony + Linear | Alessio Fanelli (Kernel Labs)

    Alessio Fanelli, founder of Kernel Labs and co-host of Latent Space podcast, walks us through two very different AI workflows: (1) a fully autonomous coding setup using OpenAI Symphony + Linear, where Linear acts as a state machine and Symphony manages agents through the whole dev lifecycle with zero babysitting; (2) Codex with browser access searching eBay for underpriced Pokémon cards—autonomously browsing, extracting PSA certificate numbers, and flagging deals on $10K–$20K cards for his San Carlos card shop, Merlin Games. What you’ll learn: Why “agent manager” is a better mental model than “agent prompter”Why local Mac Minis don’t scale, and what a cloud VPS unlocksHow to wire Symphony and Linear together as an agent state machineHow to track token costs per task (and what 221 million tokens buys you)What Glimpse does, and why better agent senses extend autonomous runsWhy your CLAUDE.md probably needs a full purge, not more instructionsHow Codex scouts underpriced $10K Pokémon cards on eBay at scaleThe new category of small business that AI just made possible— Brought to you by: Firecrawl—Power AI agents with clean web data Jira Product Discovery—Prioritize with insights, build with confidence — In this episode, we cover: (00:00) Intro (02:24) Prompter vs. agent manager (04:31) Live demo: Symphony + Linear (09:31) Setting up Symphony (14:15) Purging your skills files (18:06) The benefits of this system (19:10) Demo: Using Codex to hunt for Pokémon cards (24:17) The benefit of AI for small businesses (28:23) Lightning round — Tools referenced: • OpenAI Codex: https://openai.com/codex • OpenAI Symphony (open-source framework): https://github.com/openai/symphony • Linear (project management/agent state machine): https://linear.app • PSA (Professional Sports Authenticator) grading: https://www.psacard.com • TCGplayer (card pricing): https://www.tcgplayer.com • eBay (used for card price scouting): https://www.ebay.com — Other references: • Meta Ray-Ban glasses: https://www.ray-ban.com/usa/ray-ban-meta-smart-glasses • The Monk and the Riddle by Randy Komisar: https://www.amazon.com/Monk-Riddle-Creating-Making-Living/dp/1578516447/ref=sr_1_1 • The Divine Comedy by Dante Alighieri: https://www.amazon.com/dp/0451208633 • AS Roma (football club Alessio and Claire are both fans of): https://www.asroma.com/en — Where to find Alessio Fanelli: X: https://x.com/FanaHOVA Latent Space podcast: https://www.latent.space/ — 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.

    How I run autonomous coding agents from my phone with OpenAI Symphony + Linear | Alessio Fanelli (Kernel Labs)
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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.

Informatie

  • Maker
    Claire Vo
  • Jaren actief
    2025 - 2026
  • Afleveringen
    97
  • Beoordeling
    Expliciet
  • Copyright
    © Claire Vo
  • Website van aflevering
    How I AI
  • Provider

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