How I AI

Grace Clarke is an AI educator and former marketing consultant who taught herself Claude Code earlier this year and built a curriculum out of the process. She now runs her entire service business on tools she’s built with Claude, including a pipeline operator, a proposal maker, and a Gmail replacement she created in under 30 minutes, and teaches individuals and teams to do the same.

What you’ll learn:
How to build an hourly pipeline in Claude that moves clients through your process automatically
Why Grace ditched traditional proposals for password-protected, interactive HTML documents built in Claude
How she uses a “voice guide” skill file so every Claude output sounds like her, not like AI slop
The two-step forcing function she teaches non-technical clients to build the muscle of opening Claude
Why she started building in Claude Code, then handed the work off to Cowork via a Markdown session file
How she replaced Gmail entirely with a custom inbox
Why she teaches “intent engineering” instead of prompt engineering, and what that looks like in practice
How she uses Claude on her phone, on walks, to track workouts and manage plants alongside client work
—
Brought to you by:
Bolt.new—Turn your idea into a real product
Hyperagent—Deploy fleets of agents that handle real work
—
In this episode, we cover:
(00:00) Grace’s background and why she started building with Claude
(04:48) The pipeline operator: what it is and how it runs her business every hour
(08:48) Building the muscle memory to use AI
(12:02) What goes into building a skill file (voice guide, proposal rules, versioning)
(13:50) How she built her proposal maker
(16:15) The voice guide: teaching Claude how she thinks, not just how she writes
(21:22) Live demo of the custom Gmail replacement built in Cowork
(30:44) Workout tracking, plant photos, and tiny daily Claude habits
(34:51) The biggest misconception holding people back from adopting AI
(38:36) What Grace does when Claude is not giving her what she wants
(40:38) Claude builds a proposal for Claire in real time
—
Tools referenced:
• Claude: https://claude.ai
• Claude Code: https://claude.ai/code
• Netlify: https://www.netlify.com
• Google Forms: https://forms.google.com
• Google Sheets: https://sheets.google.com
• Google Cloud (for service accounts and custom connectors): https://cloud.google.com
—
Other reference:
• Stratechery by Ben Thompson: https://stratechery.com
—
Where to find Grace Clarke:
LinkedIn: https://www.linkedin.com/in/gracegclarke/
X: https://x.com/graceclarke
—
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.

AI writes most of my code now, and that created a new problem: a PR queue I couldn’t keep up with. In this episode, I walk through how I built Merge Mommy, a Vercel Eve agent that reads every PR after checks pass, scores it across six risk dimensions, auto-approves the low-risk ones, and pings me in Slack for anything that needs a human. I built the whole thing in one Codex session, it’s SOC 2 compatible, and it’s already cleared my backlog.

What you’ll learn:
Why AI-generated PRs create a review bottleneck and why the answer isn’t reviewing all of them
How Intercom 5x’d PR approval speed and reduced revert rates by putting AI in the review loop
Why Vercel Eve is the simplest framework I’ve found for deploying AI agents in Slack and GitHub
How I built a full PR review agent in Codex with one prompt and a few steering turns
The six components I use to score PR risk (blast radius, reversibility, data security, ops impact, verification gap, and change surface)
How I used Chrome browser use to handle Slack bot and GitHub app configuration so I never had to click through setup screens manually
Why auto-approved PRs can be SOC 2 compliant as long as the process is auditable, queryable, and in your risk policy
How to set up Slack escalation so low-risk PRs become a two-click merge with no manual review
—
Brought to you by:
WorkOS—Make your app Enterprise Ready today
—
In this episode, we cover:
(00:00) The PR review backlog problem nobody’s talking about
(02:35) Why you don’t have to review every AI-generated PR
(05:14) How Intercom built AI-approved PRs (and proved they’re safer)
(06:10) How the Eve framework works (directory, skills, channels, connectors)
(09:16) The Codex prompt I used to build the entire bot
(11:36) What the agent actually does: read, score, approve, or escalate
(13:07) Setting up your Eve agent
(15:47) The six-component risk scoring model
(17:23) Merge Mommy in action: three live PR examples
(21:10) Recap and how to build your own version
—
Tools referenced:
• Vercel Eve: https://vercel.com/eve
• Vercel AI SDK: https://sdk.vercel.ai/
• Vercel Chat SDK: https://chat-sdk.dev/
• Codex (OpenAI): https://openai.com/codex
—
Other references:
• AI is approving our pull requests: Here’s how we made it safe: https://www.intercom.com/blog/ai-is-approving-our-pull-requests-heres-how-we-made-it-safe/
—
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.

Nick Baumann is on the Developer Experience team at OpenAI, where he spends his days building with, testing, and communicating the capabilities of ChatGPT Codex and ChatGPT Work. In this episode, Nick walks me through several features that have launched or evolved recently: the new voice interface with its screen-reading orb, the Heartbeats automation system in ChatGPT Work on mobile, the live ChatGPT Sites deployment feature, and his personal use case for AI-assisted UGC video editing.

What you’ll learn:
How two-person voice chat works
How Heartbeats work
How to build and deploy a live website with ChatGPT Sites
How to delegate a flight search, hotel booking, and expense report to Codex in a single voice conversation without opening a single app manually
Why ChatGPT Work on mobile is the most underutilized AI workflow for people already using the ChatGPT app
How to use a custom UGC Video plugin to feed 50 raw clips into ChatGPT, let it pull transcripts, pick the best takes, and assemble a finished vertical video overnight
—
Brought to you by:
Bolt.new—Turn your idea into a real product
Hyperagent—Deploy fleets of agents that handle real work
—
In this episode, we cover:
(00:00) Introduction to Nick Baumann
(02:56) What’s new in Codex
(05:40) ChatGPT Work and Heartbeats
(06:40) Live Codex voice demo
(13:25) Latency vs. intelligence
(14:36) Quick recap
(15:04) Voice on mobile and the ChatGPT Sites workflow
(21:24) Live UGC video demo
(32:30) How I AI website results
(34:04) Lightning round and final thoughts
—
Tools referenced:
• ChatGPT Codex: https://chatgpt.com/codex
• ChatGPT Sites: https://chatgpt.site
—
Where to find Nick Baumann:
LinkedIn: linkedin.com/in/nick--baumann
—
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.

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 Bluetooth
How to use Cursor’s agent view to brainstorm a hardware project
What belongs in a personal API and why agents, not just humans, will be the ones using it
How to read just enough code to do some damage, without needing to understand all of it
Why 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.

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 now
How Opus 5’s “neurotic” personality showed up in real coding sessions, including a merge conflict it refused to touch
What 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 leaderboard
The one use case where Opus 5 earned straight 5s from me
My 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.