How I AI

Hilary Gridley is an entrepreneur, former product leader, and new mom who previously appeared on the podcast discussing AI for managers. She returns to share how she's transformed her approach to personal productivity using Claude Code as her primary tool for managing both professional work and life admin. Hilary demonstrates her "anti-system system"—a philosophy that prioritizes simplicity over complex setup, allowing AI to learn preferences through observation rather than upfront configuration.

What you’ll learn:
How to capture to-dos instantly using a simple iPhone back-tap shortcut that requires zero app switching
The “10x impact framework” for deciding what tasks to automate versus where to invest your human effort
How to use Claude Code’s observation capabilities to build a preference file that improves over time without manual setup
Why the “yappers API” (talking about what you’re doing while working) eliminates the need for complex OAuth integrations
A workflow for breaking down overwhelming tasks into 10-minute first steps that actually get completed
How to create Claude Skills by simply describing problems rather than writing code or following tutorials
Techniques for using “recording mode” to demo workflows without exposing personal information
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Brought to you by:
WorkOS—Make your app Enterprise Ready today
Lovable—Build apps by simply chatting with AI
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In this episode, we cover:
(00:00) Introduction to Hilary Gridley
(02:43) The opportunity cost of time as a new mom and entrepreneur
(07:11) Philosophy of the anti-system system
(08:05) Demo: Planning your day with Claude Code
(10:00) Setting up simple iPhone shortcuts for task capture
(11:48) How Claude organizes reminders and learns preferences automatically
(16:19) Breaking down overwhelming tasks into manageable first steps
(23:40) The yappers API: talking to Claude instead of building integrations
(25:28) Daily logging and observation patterns
(27:45) Quick summary
(30:50) The power of screenshots
(32:55) 10x impact framework for automation decisions
(37:51) Applying the framework to different career stages
(39:29) Building a “recording on” skill for anonymizing demos
(44:11) Building a returns tracking skill from scratch
(48:31) Building the muscle memory to reach for AI tools
(50:18) Where to find Hilary
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Tools referenced:
• Claude Code: https://claude.ai/code
• Obsidian: https://obsidian.md/
• iPhone Shortcuts: https://support.apple.com/guide/shortcuts/welcome/ios
• Cursor: https://cursor.sh/
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Other references:
• Figma file Hilary demo’ed: https://www.writerbuilder.com/howiai
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Where to find Hilary Gridley:
Substack: https://hills.substack.com/
Website: https://writerbuilder.com
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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].

Steve Kaliski is a software engineer at Stripe who has spent the past six and a half years building developer tools and payment infrastructure. He’s part of the team that created “minions”—Stripe’s internal AI coding agents, which now ship approximately 1,300 pull requests per week with minimal human intervention beyond code review. In this episode, Steve demonstrates how Stripe engineers activate development work from Slack and leverage cloud-based development environments for parallel agent workflows, and demos machine-to-machine payments where AI agents transact autonomously with third-party services.

What you’ll learn:
How Stripe’s “minions” write 1,300 pull requests per week with minimal human intervention
Why a good developer experience for humans creates better outcomes for AI agents
The critical role of cloud development environments in unlocking AI-powered engineering velocity
The machine payment protocol that lets AI agents spend money to accomplish tasks
The code review strategy for handling thousands of agent-written PRs
Why non-engineers at Stripe are starting to use minions to ship code
The future of software businesses built primarily for agent consumers
—
Brought to you by:
Optimizely—Your AI agent orchestration platform for marketing and digital teams
Rippling—Stop wasting time on admin tasks, build your startup faster
—
In this episode, we cover:
(00:00) Introduction to Steve
(02:39) Stripe’s minions and their effect on Stripe as a whole
(04:42) Why activation energy matters more than execution
(05:44) What is a minion? The technical architecture
(06:52) Demo: Activating a minion from Slack with an emoji
(09:04) Why good developer experience benefits both humans and agents
(11:22) Walking through the agent loop and system prompts
(13:42) Why Stripe chose Goose as their agent harness
(16:00) The role of Stripe’s developer productivity team
(17:15) Why cloud environments unlock multi-threaded AI engineering
(21:14) One-shot prompting: from Slack to shipped PR
(22:04) How Stripe handles code review for 1,300 AI-written PRs weekly
(23:44) Non-engineers using minions across the company
(24:53) Demo: Planning a birthday party with Claude and machine payments
(32:15) Quick recap
(35:08) The future of ephemeral, API-first businesses for agents
(36:36) Lightning round and final thoughts
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Detailed workflow walkthroughs from this episode:
• How Stripe's AI 'Minions' Ship 1,300 PRs Weekly from a Slack Emoji: https://www.chatprd.ai/how-i-ai/stripes-ai-minions-ship-1300-prs-weekly-from-a-slack-emoji
• How to Build an Autonomous AI Agent That Pays for Services to Complete Tasks: https://www.chatprd.ai/how-i-ai/workflows/how-to-build-an-autonomous-ai-agent-that-pays-for-services-to-complete-tasks
• How to Automate Code Generation from a Slack Message into a Pull Request: https://www.chatprd.ai/how-i-ai/workflows/how-to-automate-code-generation-from-a-slack-message-into-a-pull-request
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Tools referenced:
• Goose (AI agent harness): https://github.com/block/goose
• Claude Code: https://claude.ai/code
• Cursor: https://cursor.sh/
• VS Code: https://code.visualstudio.com/
• Slack: https://slack.com/
• Browserbase: https://browserbase.com/
• Parallel AI: https://www.parallel.ai/
• PostalForm: https://postalform.com/
• Stripe Climate: https://stripe.com/climate
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Other references:
• Stripe machine payments: https://docs.stripe.com/payments/machine
• Blue-Green Deployment: https://martinfowler.com/bliki/BlueGreenDeployment.html
• Git worktrees: https://git-scm.com/docs/git-worktree
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Where to find Steve Kaliski:
Twitter: https://twitter.com/stevekaliski
LinkedIn: https://www.linkedin.com/in/steve-kaliski-079a7710/
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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].

Marco Casalaina, VP of Core AI Products and AI Futurist at Microsoft, demonstrates how he uses AI tools to automate administrative tasks that typically consume valuable time. Rather than using Warp as a coding assistant (its primary marketed purpose), Marco leverages it to manage Azure resources, scan documents, compress videos, and more. He shows how these “micro-agents” can reduce friction in everyday workflows, allowing him to focus on higher-value activities. Marco also demonstrates how Microsoft 365 Copilot and ChatGPT can create triggered workflows that respond to emails or check for information on a schedule, highlighting how the line between consuming and building AI agents is blurring.

What you’ll learn:
How to use Warp to manage Azure resources and assign permissions without navigating complex web interfaces
Techniques for automating document scanning and processing directly from the terminal
Methods for analyzing and compressing video files using AI-generated FFmpeg commands
How to create simple rules that dramatically improve AI performance for specialized tasks
Ways to build triggered workflows in Microsoft 365 Copilot that automatically respond to emails
How to configure ChatGPT to perform scheduled tasks like checking for new content
Strategies for creating consistent AI interactions using AutoHotkey shortcuts
—
Brought to you by:
Rovo—AI that knows your business
Lovable—Build apps by simply chatting with AI
—
In this episode, we cover:
(00:00) Introduction to Marco Casalaina
(02:14) Why Marco chose Warp for administrative tasks
(03:57) Demo: Using Warp to manage Azure resources and permissions
(06:00) How CLI tools eliminate GUI friction for complex tasks
(07:18) Creating rules to improve AI performance for specialized tasks
(10:28) Demo: Document scanning automation
(13:00) Combining odd and even pages using a Python automation
(15:04) The value of ephemeral AI solutions vs. permanent tools
(17:12) Video compression using FFmpeg commands
(20:22) The concept of “ad hoc agents” for specific tasks
(22:31) Demo: Creating triggered workflows in Microsoft 365 Copilot
(25:51) Demo: Setting up scheduled tasks in ChatGPT
(27:17) How AI automation changes time management
(29:14) Teaching AI skills to the next generation
(30:30) Strategies for improving AI performance with AutoHotkey
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Detailed workflow walkthroughs from this episode:
• How Microsoft's AI VP Automates Everything with 5 Micro-Agent Workflows: https://www.chatprd.ai/how-i-ai/microsofts-ai-vp-automates-everything-with-5-micro-agent-workflows
How to Create an Automated Meeting Scheduler with Microsoft • 365 Copilot: https://www.chatprd.ai/how-i-ai/workflows/how-to-create-an-automated-meeting-scheduler-with-microsoft-365-copilot
• How to Scan and Merge Two-Sided Documents into a Single PDF with AI: https://www.chatprd.ai/how-i-ai/workflows/how-to-scan-and-merge-two-sided-documents-into-a-single-pdf-with-ai
• How to Automate Azure User Role Management with AI in the Terminal: https://www.chatprd.ai/how-i-ai/workflows/how-to-automate-azure-user-role-management-with-ai-in-the-terminal
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Tools referenced:
• Warp: https://www.warp.dev/
• Microsoft Azure: https://azure.microsoft.com/en-us
• Azure CLI: https://learn.microsoft.com/en-us/cli/azure/
• Microsoft 365 Copilot: https://www.microsoft.com/en-us/microsoft-365/copilot
• ChatGPT: https://chat.openai.com/
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Other references:
• NAPS2: https://www.naps2.com/
• PyPDF2: https://pypdf2.readthedocs.io/
• FFmpeg: https://ffmpeg.org/
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Where to find Marco Casalaina:
LinkedIn: https://www.linkedin.com/in/marcocasalaina/
—
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].

Daniel Roth, editor in chief at LinkedIn, went from business writer to iOS app developer, without ever learning how to code. Using Claude Code, Daniel built and shipped multiple production-ready iOS apps to the App Store, including Commutely, a personalized train-tracking app for New York commuters.

What you’ll learn:
How to set up a dual-agent Claude Code system (builder + reviewer)
Why being a “picky customer” is the right mindset for non-technical builders
How Daniel prioritizes features using AI-ranked impact vs. build time
Why saving everything as Markdown files creates long-term context
The importance of branch-based development—even when AI writes the code
How Daniel ships to the App Store without formal engineering experience
His end-of-day “What did I drop the ball on?” Copilot workflow
—
Brought to you by:
WorkOS—Make your app enterprise-ready today
Vanta—Automate compliance and simplify security
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In this episode, we cover:
(00:00) Introduction to Daniel Roth
(02:46) Daniel’s AI development workflow overview
(05:56) Using Claude to prioritize feature ideas
(08:58) Building vs. marketing
(09:47) Creating a retention plan for his app
(10:38) Introducing Bob the Builder and Ray the Reviewer
(13:50) How Bob and Ray work together to build features
(14:37) Why Daniel focuses on learning the process
(16:34) The importance of using branches for development
(17:39) Managing AI agents like managing a team
(21:12) Navigating the App Store
(23:06) Being a “picky customer” rather than a PM
(25:00) Testing in Xcode and shipping to the App Store
(28:14) Quick recap
(30:00) Creating terminal aliases with Claude
(31:38) Demo of his Commutely app
(32:10) Using Copilot to manage work responsibilities
(35:05) How Daniel talks to AI without personifying it
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Tools referenced:
• Claude: https://claude.ai/
• Claude Code: https://claude.ai/code
• Cursor: https://cursor.sh/
• Xcode: https://developer.apple.com/xcode/
• Canva: https://www.canva.com/
• Microsoft Copilot: https://copilot.microsoft.com/
• Terminal: https://support.apple.com/guide/terminal/welcome/mac
• Obsidian: https://obsidian.md/
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Other reference:
• Commutely (iOS app): https://apps.apple.com/us/app/commutely/id6755789873
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Where to find Daniel Roth:
LinkedIn: https://www.linkedin.com/in/danielroth1/
Newsletter: https://www.linkedin.com/newsletters/forward-deployed-editor-7378272989982683137/
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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].

Most teams are still passing static design files back and forth, and most Figma files are already out of date by the time they reach engineering. Gui Seiz (designer) and Alex Kern (engineer) from Figma walk through the exact workflow their team uses to bridge that gap with AI, live onscreen. They demo how to pull a running web app directly into Figma using the Figma MCP, edit it collaboratively, and push it back to code. The old linear waterfall workflow is gone. What replaces it is a fluid, bidirectional loop where design and code inform each other in real time.

What you’ll learn:
How to use Figma’s MCP to pull production code directly into Figma files
A workflow for pushing design changes from Figma back into your codebase using Claude Code without manual CSS adjustments
How to export multiple code states (like all five states of a signup flow) into Figma so designers can work with what actually exists in production
Why AI has shifted design work upstream to planning and downstream to craft, eliminating the rushed middle phase of execution
How to create custom skills that automate pre-flight checks, lint fixes, and CI monitoring before pushing code to production
How to structure your codebase so AI can write 90% of your code more effectively
—
Brought to you by:
Optimizely—Your AI agent orchestration platform for marketing and digital teams
—
In this episode, we cover:
(00:00) Introduction to Gui and Alex from Figma
(02:56) How AI has transformed Figma’s internal workflows
(05:17) The collapse of linear design-to-code workflows
(07:28) Demo: Pulling production code into Figma using MCPs
(10:49) Using Figma for precise design manipulation and team collaboration
(14:10) Demo: Pushing Figma designs back into code with Claude Code
(16:06) How AI has changed the role of software engineers
(18:43) The shift to upstream planning and downstream craft
(22:31) Demo: Exporting multiple code states back into Figma
(25:23) Synchronous vs. asynchronous collaboration with AI
(28:00) Eliminating design and engineering toil with AI
(29:03) Demo: Custom skills for automating pre-flight checks
(34:06) Code first or design first?
(35:24) Using AI to learn and explore codebases
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Tools referenced:
• Figma: https://www.figma.com/
• From Claude Code to Figma: Turning production code into editable Figma designs: https://www.figma.com/blog/introducing-claude-code-to-figma/
• Codex: https://codex.ai/
• Claude Code: https://claude.ai/code
• Buildkite: https://buildkite.com/
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Other references:
• Balsamiq: https://balsamiq.com/
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Where to find Gui Seiz:
X: https://x.com/guiseiz
LinkedIn: https://www.linkedin.com/in/guiseiz/
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Where to find Alex Kern:
X: https://x.com/kernio
LinkedIn: https://www.linkedin.com/in/alexanderskern/
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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].