How I AI

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 accounts
How to safely limit Clawdbot’s permissions while still making it useful
Why Clawdbot struggles with basic time concepts but excels at research tasks
The future of AI assistants—and who might build the consumer-friendly version
How to use voice messaging with AI agents for on-the-go productivity
Why latency is one of the biggest challenges for autonomous AI assistants
—
Brought to you by:
Lovable—Build apps by simply chatting with AI
—
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 [email protected].

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 assistance
Creating custom hooks in Claude Code to automatically check for TypeScript errors and commit working code
Building efficient command-line aliases and tools to streamline your AI workflows
Techniques for using AI to generate documentation that works for both humans and machines
How to leverage AI for code investigation and orientation when tackling unfamiliar codebases
Strategies 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 [email protected].

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 needs
Why she moved from Trello to a markdown-based system that gives her complete control and searchability
How she automated academic research collection with daily digests of relevant papers
Her strategy for organizing context files to make Claude more effective without overwhelming it
Why “pair programming” with Claude has become her approach to everything from writing to task management
How she uses Claude as a writing partner while maintaining her authentic voice
The 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 [email protected].

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 tasks
A practical workflow for running multiple Codex instances in parallel using Git worktrees to avoid conflicts
How to create detailed implementation plans using the Plans.md technique for complex engineering projects
Why context is critical when prompting Codex—and how to provide the right information for better results
How OpenAI uses automated code review to accelerate development while maintaining high quality standards
The key differences between vibe coding for prototypes versus building production-ready applications with AI
How 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 [email protected].

Wade Foster is the co-founder and CEO of Zapier. In this episode, Wade shows how he uses meeting transcripts, Zapier agents, and even Grok to analyze company culture, evaluate interview candidates, and source talent from unexpected places. He explains why CEOs need to lead by example when it comes to AI adoption and shares practical workflows that any executive can implement to make hiring more effective and efficient.

What you’ll learn:
How to use meeting transcripts to extract your company’s “unspoken culture” and compare it against your stated values
A workflow for creating AI interview evaluators that assess candidates against your job descriptions and company values
How to use Zapier agents to provide objective feedback on candidate interviews while checking your own biases
Why CEOs should participate in AI “hackathons” and “show and tells” rather than just delegating AI adoption
A surprising technique for using Grok to find “diamonds in the rough” talent outside traditional recruiting channels
How AI enables companies to complete tasks that were previously not economically viable
—
This entire episode is brought to you by:
Brex—The intelligent finance platform built for founders
—
In this episode, we cover:
(00:00) Introduction to Wade Foster
(02:32) Zapier’s AI adoption
(06:50) Creating AI fluency rubrics
(08:37) Using Granola to extract company culture from meeting transcripts
(10:49) Practical use cases for company culture rubrics
(13:38) Building an AI interview evaluation agent in Zapier
(16:50) Using Copilot to improve agent prompts
(18:49) Ideas for enhancing the interview agent
(22:31) Mistakes people make when using agents
(25:11) Using Grok to find talent on social media platforms
(33:39) Recap of AI workflows for recruiting and hiring
(34:40) Lightning round and final thoughts
—
Tools referenced:
• Zapier: https://zapier.com/
• Zapier Agents: https://zapier.com/agents
• Granola: https://granola.ai/
• Grok: https://grok.x.ai/
• ChatGPT: https://chat.openai.com/
• Copilot: https://copilot.microsoft.com/
—
Other references:
• Zapier values: https://zapier.com/about
• How Zapier’s EA built an army of AI interns to automate meeting prep, strengthen team culture, and scale internal alignment | Cortney Hickey: https://www.lennysnewsletter.com/p/how-zapiers-ea-built-an-army-of-ai
• How this CEO turned 25,000 hours of sales calls into a self-learning go-to-market engine | Matt Britton (Suzy): https://www.lennysnewsletter.com/p/how-this-ceo-turned-25000-hours-of
—
Where to find Wade Foster:
Zapier: https://zapier.com/
LinkedIn: https://www.linkedin.com/in/wadefoster/
X: https://twitter.com/wadefoster
—
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].