
Show Notes
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 is When to build a harness versus when to stick with a general-purpose tool like Claude Code or Codex How to encode specific permissions into a harness The three components every harness needs How 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 [email protected].
More from How I AI
Anthropic's new personal agent, Claude Duet, lives on your phone, inherits all your Claude plugins and connectors, and is pitched at small business owners and busy professionals. It's the most polished agent launch I've seen: thoughtful onboarding, task lists, first-class artifacts, and Slack-style channels. But polish isn't enough when you're competing with every other personal agent for attention. I put it to work on my inbox and Slack, my sales pipeline, a Google Docs sales deck, a launch video, and finding Warriors tickets for my kids, and I'll walk you through what it nails, where it stalls, and what Anthropic needs to fix before it can become anyone's number one agent.
Brooke Lacey has been making videos since before Facebook had video, and she built a TikTok audience of more than 290,000 by learning to cut short-form videos herself. With over 25 years in tech, she now builds her own apps, including Zosha, a free mobile app for learning AI. In this episode, Brooke walks me through the Claude Code, FFmpeg, and Whisper workflow that edits her TikToks in about 15 seconds, how she mines her comments for new scripts, and how she runs a weekly short-form operation with no editor.
I put Meta’s new Muse Wonder (and Wonder Full) frontier models through the How I AI bench, which covers nearly 20 tasks across prototyping, agentic workflows, coding, writing, and creative work. I scored everything with an LLM-as-a-judge pass and my own voice notes, then pulled together the first-look results you see here.
Alex Cornell is a design director at Meta, where he leads design on Muse, Meta’s consumer AI agent. He came to the role with a long background in software product design, including time as a founder, and has spent the past year building one of the most thoughtful agent interfaces in the consumer AI space. Muse ships with a custom avatar, a three-layer status display, a personalized ideas surface, and a generative feed. Alex has been sharing the reasoning behind each of those design decisions publicly on Threads.
Kath Korevec is a member of the Product staff at OpenAI working on Codex, and she spent over a year building and using ChatGPT Sites internally before its public launch. She’s been on the front lines of shipping Plugin Insights, MCP plugin hosting, and the connector ecosystem, which now includes around 60 integrations.