What is an AI harness? I build one live in less than 30 minutes

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:* 1. What a harness actually is 2. When to build a harness versus when to stick with a general-purpose tool like Claude Code or Codex 3. How to encode specific permissions into a harness 4. The three components every harness needs 5. How I used GPT-5.5 and Claude Opus to build the harness code itself (and where they both initially resisted) 6. 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: https://bolt.new/partner/howiai Customer.io—Build customer engagement campaigns from a single prompt: https://www.customer.io/howiai *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 jordan@penname.co._

Claire Vohost

Jul 8, 202624mWatch on YouTube ↗

EPISODE INFO

Released: July 8, 2026
Duration: 24m
Channel: How I AI
Watch on YouTube: ▶ Open ↗

EPISODE DESCRIPTION

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: https://bolt.new/partner/howiai Customer.io—Build customer engagement campaigns from a single prompt: https://www.customer.io/howiai *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 jordan@penname.co._

SPEAKERS

Claire Vo
host
Host of the podcast 'How I AI with Claire Vo' focused on practical AI workflows and tools.

EPISODE SUMMARY

In this episode of How I AI, featuring Claire Vo, What is an AI harness? I build one live in less than 30 minutes explores demystifying AI harnesses: build a bug-triage agent around Claude SDK A harness is simply code wrapped around an AI agent to make it more effective for a specific job by enforcing context, allowed actions, and expected outcomes.

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