How I AI

Bryce Rattner Keithley has spent her career in talent and recruiting, working with technical leaders but never writing a line of code herself. Yet she managed to build Daily Hundred—a fitness app featuring custom AI-generated videos of anthropomorphic animals demonstrating exercises—and ship it to the App Store before her software engineer friends. Using Replit, Claude, Gemini, and a relentless beginner’s mindset, Bryce proves that in the AI era, execution is no longer the constraint on good ideas.

What you’ll learn:

1. How to build and ship an iPhone app using Replit without any coding knowledge
2. The step-by-step process for creating custom AI-generated workout videos by combining Gemini images with real exercise footage
3. How to use Claude as your technical architect and Claude Code as your software engineer
4. How to navigate App Store submission requirements (including fixing rejection feedback)
5. Why being hyper-literal in your prompts unlocks better AI results
6. Why a beginner’s mind is actually an advantage when building with AI tools

—

Brought to you by:

WorkOS—Make your app enterprise-ready today

Metaview—The agentic recruiting platform for winning teams

—

In this episode, we cover:

(00:00) Introduction to Bryce and Daily Hundred

(04:48) Building with Replit

(06:16) The beginner’s mindset advantage

(11:17) Creating anthropomorphic animals

(22:55) Moving from static image to video

(27:15) The floating genie and other anthropomorphic animal generations

(30:46) Shifting from web app to App Store submission

(36:24) User feedback

(37:41) Lightning round and final thoughts

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Tools referenced:

• Replit: https://replit.com/

• Lovable: https://lovable.dev/

• Claude: https://claude.ai/

• Claude Code: https://claude.ai/code

• Gemini: https://gemini.google.com/

• Higgsfield: https://higgsfield.ai/

• Kling: https://kling.ai/

• Railway: https://railway.app/

• TestFlight: https://developer.apple.com/testflight/

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Other references:

• How a 91-year-old vibe coded a complex event management system using Claude and Replit | John Blackman: https://www.lennysnewsletter.com/p/how-a-91-year-old-vibe-coded-a-complex

• What Got You Here Won’t Get You There: https://www.amazon.com/What-Got-Here-Wont-There/dp/1401301304

• How Women Rise: https://www.amazon.com/How-Women-Rise-Holding-Careers/dp/0316440124

• A Whole New Mind: https://www.amazon.com/Whole-New-Mind-Right-Brainers-Future/dp/1594481717

• How to Win Friends and Influence People: https://www.amazon.com/How-Win-Friends-Influence-People/dp/0671027034

—

Where to find Bryce Rattner Keithley:

LinkedIn: https://www.linkedin.com/in/brycerattner/

GitHub: https://github.com/brk-bot/

Daily Hundred on the App Store: https://apps.apple.com/us/app/daily100-fitness-challenge/id6762108062

—

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 [email protected].

I got a few hours of early-access testing with Anthropic’s newly released model Opus 4.8. I walk through real coding, design, and strategy tasks across Claude Code and Claude Cowork, and give you my unfiltered view on what impressed me and what didn’t.

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What you’ll learn:

1. Where Opus 4.8 excels: greenfield prototypes, one-shot features, and fast execution
2. Where it struggles: the last 10%, edge cases in existing codebases, and hallucinations
3. How Opus 4.8 compares to Opus 4.7 on business strategy work
4. Why I’m still reaching for Opus 4.7 on data-heavy strategy and roadmap work
5. The new features shipping alongside the model: dynamic workflows with parallel subagents and effort control in Claude.ai and Cowork
6. The prompting and harness strategy I’d use to get the most out of it

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In this episode, we cover:

(00:00) Introduction to Opus 4.8 

(00:44) Benchmark performance and pricing

(01:53) First coding test: Building a prototyping tool

(03:00) Where it failed: The last 10% problem

(03:27) The hallucination problem

(04:23) Testing Opus 4.8 on existing codebases

(05:24) The ambition test: Building games for a 9-year-old

(07:03) Business strategy test: 4.7 vs 4.8

(08:23) The roadmap test

(09:17) Final verdict

—

References:

• System Card: Claude Opus 4.8: https://cdn.sanity.io/files/4zrzovbb/website/c886650a2e96fc0925c805a1a7ca77314ccbf4a6.pdf

• Introducing Claude Opus 4.8 on X: https://x.com/claudeai/status/2060042702150930686?s=20

—

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 [email protected].

In this 30-minute episode, I walk through my favorite feature in Codex: the /goal command. I show how Goals transform AI from a turn-based assistant that needs constant ‘what’s next?’ prompting into an autonomous agent that can work for hours on complex, multi-step tasks. I share three real examples: eliminating thousands of Sentry errors, cleaning 3,900 emails down to 68, and organizing hundreds of Linear tasks.

What you’ll learn:

1. What Goals are and how they differ from standard prompts
2. How I used /goal to eliminate hundreds of error logs in my codebase over a five-hour autonomous run
3. The non-technical use cases that make Goals incredibly powerful: cleaning up 3,900 emails in under four hours and organizing hundreds of project management tasks in Linear
4. How to write effective /goal prompts with measurable outcomes, verification methods, and constraints
5. When not to use Goals and what makes a strong versus weak Goal
6. Why Goals represent a fundamental shift in how we work with AI, from babysitting the model to managing it

—

Brought to you by:

Mercury—Radically different banking loved by over 300K entrepreneurs

—

In this episode, we cover:

(00:00) Introduction

(01:50) What is /goal and when should you use it?

(02:45) The difference between prompts and Goal-based loops

(04:06) Claire’s first five-hour 45-minute autonomous coding task

(05:05) How to manage a Goal lifecycle: view, pause, resume, and clear

(06:06) How to write strong goals: outcomes vs. outputs

(07:34) The six components of effective Goals

(08:57) Example: Reducing P95 checkout latency with /goal

(09:36) Demo: Using /goal to eliminate Sentry errors in ChatPRD

(13:18) Demo: Burning down Vercel API errors

(17:28) Non-technical use case: Cleaning 3,900 emails with /goal

(21:24) Demo: Using /goal to clean up Linear project tasks

(24:41) When not to use /goal

(26:10) Why /goal changes everything

—

Tools referenced:

• Codex: https://openai.com/codex/

• Sentry: https://sentry.io/

• Vercel: https://vercel.com/

• Linear: https://linear.app/

—

Other reference:

• OpenAI blog post “Using Goals in Codex”: https://developers.openai.com/cookbook/examples/codex/using_goals_in_codex

—

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 [email protected].

Felix Rieseberg is the engineering lead for Claude Cowork and Claude Code Desktop at Anthropic. He previously spent five years at Slack building developer tools. In this episode, Felix demonstrates how he uses Claude to solve real-life problems: analyzing floor plans to build interactive 3D house walkthroughs, automatically tracking promises he makes on Twitter, and building a $20 hardware device that physically approves Claude actions with a button press.

What you’ll learn:

1. How to use Claude Cowork to turn a 2D floor plan into an interactive 3D walkthrough where you can move furniture around
2. The “go one abstraction layer up” philosophy: why you should never manually enter data Claude can find itself
3. How to use your email as an inventory database for furniture, clothing, and personal purchases
4. When to use Opus vs. Sonnet 4.6 (hint: it’s about how well you can scope the problem, not technical complexity)
5. How live artifacts work and why they’re powerful for dashboards that refresh with real-time data from your connectors
6. The product philosophy behind making latency delightful
7. How to build your own $20 hardware device using Claude Code (no hardware experience required)
8. Why Felix never reads the code Claude writes and judges it purely on output

—

Brought to you by:

Magic Patterns—Prototypes that look like your product

Guru—The AI layer of truth

—

In this episode, we cover:

(00:00) Introduction to Felix Rieseberg

(02:40) Felix’s role at Anthropic

(03:25) The multiple tabs in Claude and why they exist

(05:55) Using Claude Cowork to design a new house using floor plans

(09:52) When to use Opus versus Sonnet 4.6

(12:37) Building an interactive 3D furniture planner

(14:30) Using your email as a source of truth for personal inventory

(15:58) The anti-to-do list: going one abstraction layer up

(23:14) Introduction to live artifacts

(26:02) Building a personal dashboard with live data

(28:37) Being polite to Claude (and why it matters for your humanity)

(30:28) Claude interaction tips

(32:33) Looking at the daily dashboard

(33:55) How live artifacts work with connectors

(35:02) Redesigning the dashboard

(37:55) The biggest gap: people don’t know what problems AI can solve

(41:52) The reverse interview

(42:30) Making latency delightful through asynchronous design

(44:05) The redesigned dashboard

(45:28) AI should free up your creative energy

(46:44) Building a $20 hardware Claude buddy

(52:33) Why kids are magical AI users

(54:30) Recap and final thoughts

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Tools referenced:

• Claude Cowork: https://www.anthropic.com/product/claude-cowork

• Claude Code: https://claude.ai/code

• Claude for Chrome: https://code.claude.com/docs/en/chrome

• Claude Desktop: https://claude.ai/download

• Live Artifacts: https://support.claude.com/en/articles/14729249-use-live-artifacts-in-claude-cowork

• Connectors (Spotify, Gmail, Calendar, Notion): https://claude.ai/settings/connectors

• Slack: https://slack.com/

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Where to find Felix Rieseberg:

Website: https://felixrieseberg.com/

LinkedIn: https://www.linkedin.com/in/felixrieseberg/

X: https://x.com/felixrieseberg

GitHub: https://github.com/felixrieseberg

—

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 [email protected].

Today is day one of Google I/O 2026, and I walk through every major announcement live—from the new Gemini 3.5 model family to Anti-Gravity 2.0, Google AI Studio, Gemini’s consumer redesign, the Omni video model, Flow, Stitch, and Pomelli. I test them in real time and tell you exactly which ones delivered.

What you’ll learn:

1. How Gemini 3.5 Flash benchmarks against Claude and GPT models on speed and agentic coding tasks
2. How Anti-Gravity 2.0’s new features (projects, scheduled tasks, subagents, slash commands) compare to Codex and Claude Code
3. Why the /grill-me slash command could be a more aggressive alternative to Claude Code’s clarification flow—and how to use it
4. How Google AI Studio’s new Workspace integration is designed to own the internal productivity app use case
5. How Google’s new creative tools work in practice: Omni (video generation), Flow (cinematic video editing and character consistency), Stitch (streaming UI design with inline edits), and Pomelli (brand identity and asset generation)
6. Why Google’s launch-to-availability gap is still a problem—and what to do when a featured product doesn’t actually work yet

—

Brought to you by:

Magic Patterns—Prototypes that look like your product

Thoughtspot—Build AI-powered analytics into your product

—

In this episode, we cover:

(00:00) Google I/O 2026 day 1 overview

(01:47) Gemini 3.5 flash

(04:19) Antigravity updates

(06:32) CLI test and agent features

(07:59) Core agent features released today—May 19th, 2026

(09:43) New slash commands

(11:20) Antigravity test results and takeaways

(12:25) AI Studio updates

(13:52) Access issues

(15:20) Gemini redesign

(17:24) Gemini image gen test

(19:16) Omni (video generation)

(22:56) Flow (cinematic editing)

(24:31) Avatar creation test

(26:45) Pomelli and Stitch

(31:13) Recap and final thoughts

—

Tools referenced:

• Gemini 3.5 Flash: https://deepmind.google/technologies/gemini/

• Antigravity: https://antigravity.google/

• Google AI Studio: https://aistudio.google.com/

• Google Gemini: https://gemini.google.com/

• Omni (video generation): https://gemini.google/overview/video-generation/

• Google Flow: https://flow.google/

• Stitch: https://stitch.withgoogle.com/

• Pomelli (Google brand tool): https://labs.google.com/pomelli/about/

—

Other references:

• Google I/O 2026 announcements: https://blog.google/innovation-and-ai/sundar-pichai-io-2026/

—

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 [email protected].

Thariq Shihipar is an engineer at Anthropic working on the Claude Code team. He’s spent the past several months experimenting with HTML as a replacement for Markdown in planning and implementation workflows, discovering that richer visual formats lead to better human engagement—and, ultimately, better products. In this episode, filmed at Anthropic’s Code with Claude event in San Francisco, Thariq demonstrates how to use HTML artifacts to create interactive plans, build throwaway UIs for specific problems, and maintain living design systems that travel with your codebase.

What you’ll learn:

1. Why HTML has replaced Markdown as the ideal format for AI agent communication and planning
2. How to brainstorm in HTML to get visual mockups and interactive demos instead of text lists
3. The technique for building throwaway micro-UIs to edit specific parts of your plan
4. How to create a living design system in HTML that lives in your repo and travels with every project
5. Why “complexity has to earn its keep” and how HTML helps you stay in the loop without over-constraining Claude
6. The prompting technique that gives Claude flexibility while ensuring that you get what you need
7. Why 99% of your AI-generated tokens should go to planning, interfaces, and communication—not production code

—

Brought to you by:

Celigo—Intelligent automation built for AI

Persona—Trusted identity verification for any use case

—

In this episode, we cover:

(00:00) Introduction

(02:39) HTML as the new Markdown

(04:30) The compute allocator mindset

(05:51) How HTML makes specs more engaging

(06:48) Demo: Brainstorming in HTML with Claude Code

(09:24) From brainstorm to full implementation plan

(11:20) Prompting philosophy: Trust Claude but give it constraints

(13:50) The future of PRDs and tech specs

(18:16) Making HTML specs editable

(20:23) The abundance mindset

(24:17) Just-in-time documentation and throwaway software

(25:39) Using plans as artifacts for implementation

(26:39) Demo: Living design systems in HTML

(30:16) Adding comments and annotations to HTML plans

(31:42) Recap: The HTML workflow

(32:21) Lightning round and final thoughts

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Tools referenced:

• Claude Code: https://claude.ai/code

• Claude Design: https://claude.ai/design

• AWS: https://aws.amazon.com/

• Figma: https://www.figma.com/

• GitHub: https://github.com/

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Other references:

• Anthropic Code with Claude event: https://claude.com/code-with-claude

• SpaceX partnership announcement: https://www.anthropic.com/news/higher-limits-spacex

• Jevons paradox: https://en.wikipedia.org/wiki/Jevons_paradox

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Where to find Thariq Shihipar:

Website: https://www.thariq.io/

LinkedIn: https://www.linkedin.com/in/thariqshihipar/

X: https://x.com/trq212

GitHub: https://github.com/ThariqS

—

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 [email protected].

Ryan Nystrom is a software engineer at Notion. He joined in December 2024 after Notion acquired Campsite, the team communication platform he co-founded with Brian Lovin. At Notion, he’s been a core builder of Notion AI and the Custom Agents feature launched in February 2026. He manages a team of six to seven engineers while still writing code himself, currently running Project Afterburner, a push to cut Notion’s CI time to a quarter of its current duration.

What you’ll learn:

1. How to build a Notion AI custom agent that auto-generates your daily standup pre-read by pulling from Slack, GitHub, Honeycomb metrics, and yesterday’s meeting transcript
2. How to configure subagents and MCP integrations within Notion AI
3. How Notion’s internal “Boxy” system lets engineers @mention Codex from within Notion comments and get a full pull request with screenshots in 20 minutes
4. The spec-first development workflow: dictate an idea into Whisper, have Codex format it as a proper spec, commit it to the repo, and let the agent implement and verify it autonomously
5. Why fast CI is absolutely critical in the age of AI coding agents
6. How to prompt AI coding agents to defend their reasoning under pushback
7. Why engineering managers and even senior executives should keep writing code

—

Brought to you by:

WorkOS—Make your app enterprise-ready today

Orkes—The enterprise platform for reliable applications and agentic workflows

—

In this episode, we cover:

(00:00) Introduction to Ryan Nystrom

(02:48) How AI has upended 12+ years of the same working routine

(04:30) Project Afterburner: Notion’s push to cut CI time to a quarter

(09:00) Why high-frequency, high-quality meetings beat lower-frequency standups

(11:10) How automated context surfaces every engineer’s work equally

(12:15) Why cutting meeting prep is a burnout protection mechanism

(14:26) The case for engineering managers writing code

(16:13) Inside “Boxy”: Notion’s internal VM-based background agent system

(20:30) Old World vs. New World code review

(24:51) Prompting Codex from Notion comments

(29:20) The emotions around code review

(31:01) Quick recap

(32:00) Spec-first development: writing and checking agent specs into the repo

(35:10) The spec as changelog: version control for how a feature actually works

(37:53) How engineers’ roles are evolving

(39:00) Lightning round

(45:21) Where to find Ryan

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Tools referenced:

• Notion AI: https://www.notion.com/product/ai

• Notion Custom Agents: https://www.notion.com/blog/introducing-custom-agents

• Codex (OpenAI): https://openai.com/codex

• Claude Code (Anthropic): https://claude.ai/code

• Honeycomb (observability + MCP): https://www.honeycomb.io

• Whisper (OpenAI voice transcription): https://openai.com/research/whisper

• Slack: https://slack.com

• GitHub: https://github.com

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Other references:

• How Stripe built “minions”—AI coding agents that ship 1,300 PRs weekly from Slack reactions | Steve Kaliski (Stripe): https://www.chatprd.ai/how-i-ai/stripes-ai-minions-ship-1300-prs-weekly-from-a-slack-emoji

• Notion 3.3 Custom Agents launch (February 24, 2026): https://www.notion.com/releases/2026-02-24

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Where to find Ryan Nystrom:

X: https://x.com/ryannystrom

LinkedIn: https://www.linkedin.com/in/ryannystrom/

GitHub: https://github.com/rnystrom

—

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 [email protected].

Claire breaks down the biggest announcements from Anthropic’s “Code with Claude” event and what they actually mean for builders shipping AI products today. From scheduled AI routines to outcome-based agents, multi-agent orchestration, and new memory systems, Claire walks through the features she’s most excited to use immediately—and how they could reshape the future of agentic software.

What you’ll learn:

1. How Claude Code routines let you automate recurring workflows on schedules or webhooks
2. What “Outcomes” are and how rubric-based agent grading works
3. How multi-agent orchestration enables specialized AI teams with different roles and tools
4. Why Anthropic’s new “Dreams” memory system matters for long-term agent behavior
5. Why increased Claude Code usage limits are a bigger deal than they sound
6. How Claire thinks about building practical agentic products today

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Resources:

• Code with Claude: https://claude.com/code-with-claude

• Claude Code Routines Docs: https://code.claude.com/docs/en/routines

• Define Outcomes Docs: https://platform.claude.com/docs/en/managed-agents/define-outcomes

• Dreams Docs: https://platform.claude.com/docs/en/managed-agents/dreams

• Multi-Agent Docs: https://platform.claude.com/docs/en/managed-agents/multi-agent

• Managed Agent Webhooks Docs: https://platform.claude.com/docs/en/managed-agents/webhooks#supported-event-types

• Codex (OpenAI): https://openai.com/codex

• GitHub: https://github.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 [email protected].

John Kim is the co-founder and CEO of Delight.ai, a customer experience platform that’s transforming how companies deploy AI. But what makes John’s story fascinating isn’t just his product; it’s how he’s turned his entire company into an AI-native organization. His marketing team built a fully functional e-commerce swag store with Stripe integration in days. His sales team built their own CRM tools. His recruiting team automated their entire workflow. And it’s all tracked, measured, and celebrated through an internal platform called Automators.

What you’ll learn:

1. How Sendbird’s marketing team built a fully functional swag store with Stripe integration in a day (with no engineering support)
2. How the Automators platform works—an internal marketplace where anyone can request AI tools and engineers (or AI agents) can build them
3. How to create secure, compliant templates so non-technical teams can ship to production safely
4. How Sendbird built a token usage dashboard with five tiers (beginner through AI God) and why tracking the smoothness of the curve matters more than the total
5. Why visible leadership usage is the most powerful adoption signal
6. Why Sendbird rewrote job descriptions to prioritize curiosity, agency, and energy over years of experience
7. How John uses AI for his own learning

—

Brought to you by:

WorkOS—Make your app enterprise-ready today

ThoughtSpot—Build AI-powered analytics into your product

—

In this episode, we cover:

(00:00) Introduction to John Kim

(02:45) The Delight.ai swag store built by marketing in two days

(05:51) The before times: when fun had to earn its place on the roadmap

(07:55) Demo: The Automators platform and quest system

(13:47) The AI Engineer for Internal Operations role

(16:06) Demo: The company-wide skills marketplace

(17:19) Treating AI adoption as a product

(18:43) Real wins: team-level and campaign examples

(21:51) Why SaaS isn’t dead—it’s being rebuilt internally

(23:46) Demo: The token tracking dashboard

(26:32) Measuring without fear: setting expectations, not punishments

(28:54) Quick recap

(30:51) Personal AI use cases: endless knowledge at your fingertips

(36:15) Lightning round and final thoughts

—

Tools referenced:

• Claude Code: https://claude.ai/code

• Codex (OpenAI): https://openai.com/codex

• Obsidian: https://obsidian.md

• GitHub: https://github.com

• Stripe: https://stripe.com

—

Other references:

• Jason Levin (CEO of Memelord) on How I AI: https://www.lennysnewsletter.com/p/from-a-690-newsletter-to-3m-api-how

• Konami Code: https://en.wikipedia.org/wiki/Konami_Code

• Andrew Huberman’s podcast: https://hubermanlab.com/

• Y Combinator: https://www.ycombinator.com/

—

Where to find John Kim:

X: https://x.com/doshkim

Instagram: https://instagram.com/dosh

LinkedIn: https://www.linkedin.com/in/doshkim/

Company: https://delight.ai

Delight.ai Spark Conference (May 7, SF): https://delight.ai/spark

—

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 [email protected].

Owen Williams is a design manager at Stripe who built Protodash, an internal AI-powered prototyping platform that lets designers and PMs create high-quality Stripe dashboard prototypes without writing code. What started as a bundle of Cursor rules and React components evolved into a full web-based prototyping studio that runs in dev boxes, complete with design review modes, variant testing, and AI-powered iteration. Surprisingly, PMs now use Protodash just as much as designers, fundamentally changing how Stripe approaches prototyping, design reviews, and engineering handoffs.

What you’ll learn:

1. How Stripe built an internal AI prototyping tool using Cursor rules, MCPs, and their design system
2. Why “blurple slop” happens when designers use generic AI tools—and how to fix it
3. The architecture behind Protodash: React router, design system components, and MCP integrations
4. How Stripe prototypes in dev boxes so designers never have to worry about local setup
5. Why “demos, not memos” transformed Stripe’s design review culture
6. How Stripe built design review modes, variant testing, and AI annotation directly into your prototyping tool
7. Why internal tools don’t need to be production-grade to be transformative

—

Brought to you by:

Celigo—Intelligent automation built for AI

Cursor—The best way to code with AI

—

In this episode, we cover:

(00:00) Welcome and intro to Owen Williams

(02:19) The “blurple slop” problem with AI design tools

(03:50) Protodash: an internal vibe-coding tool for Stripe prototypes

(05:26) Why an engineering background helped Owen lower the bar for designers

(07:55) The Cursor rules that taught the Stripe design system

(09:04) Running prototypes on dev boxes vs. locally

(10:30) “Demos, not memos” and rewiring design reviews at Stripe

(14:50) Building Protodash Studio: a browser-based wrapper for prototyping

(19:04) Live demo: variants, line charts, and remixing prototypes in browser

(21:02) Self-testing prototypes that take screenshots and check their work

(23:20) Multiple variant features

(26:08) The annotate-for-AI button for in-canvas feedback

(27:21) Design review mode: comments, summaries, and AI follow-up

(29:39) Why building internal tools beats buying off-the-shelf

(32:50) PMs as the surprise power users of Protodash

(35:20) Live demo: a Black Friday/Cyber Monday pet store dashboard

(42:03) Lo-fi modes, monospace fonts, and “Comic Sans for WIP” at Shopify

(44:45) Quick recap

(45:35) The Radar prototype that changed engineering handoff

(49:08) Lightning round and final thoughts

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Blog & detailed workflow walkthroughs from this episode:

Stripe’s Owen Williams on Killing ‘Blurple Slop’ with an Internal Prototyping Studio: http://chatprd.ai/how-i-ai/stripe-owen-williams-on-buildling-internal-prototyping-studio

↳ How To Connect a Design System to an AI Code Editor for High Fidelity Prototypes: https://www.chatprd.ai/how-i-ai/workflows/how-to-connect-a-design-system-to-an-ai-code-editor-for-high-fidelity-prototypes

↳ Streamline Design Reviews with an AI-Powered Prototyping Studio: https://www.chatprd.ai/how-i-ai/workflows/streamline-design-reviews-with-an-ai-powered-prototyping-studio

↳ Build a Personal AI App to Track Purchases and User Manuals: https://www.chatprd.ai/how-i-ai/workflows/build-a-personal-ai-app-to-track-purchases-and-user-manuals

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Tools referenced:

• v0: https://v0.app/

• Cursor: https://cursor.com/

• Claude Code: https://www.claude.com/product/claude-code

• Claude Design: https://www.anthropic.com/news/claude-design-anthropic-labs

• Figma: https://www.figma.com/

• Stripe Radar: https://stripe.com/radar

• Balsamiq: https://balsamiq.com/

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Where to find Owen Williams:

X: https://x.com/ow

Website: https://owenwillia.ms/

LinkedIn: https://www.linkedin.com/in/owenpwilliams

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Where to find Claire Vo:

ChatPRD: https://www.chatprd.ai/

Website: https://clairevo.com/

X: https://x.com/clairevo

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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected].