GPT-5.6 Sol is back, and I ran it through my full How I AI vibe benchmark against GPT-5.6 Terra, Luna, Claude Fable 5, and Sonnet 5 across five categories: PRDs, prototypes, wireframes, debugging, and agentic voice. Sol won by a meaningful margin on my Claire Weighted Index (70% my taste, 30% Terminal Bench 2.1), and I also tested two use cases I can't stop thinking about: building a gamified homework tracking app for my kids in one shot with Codex, and browser automation with Chrome that burned through 500 LinkedIn replies while I did literally...
GPT-5.6 Sol is back, and I ran it through my full How I AI vibe benchmark against GPT-5.6 Terra, Luna, Claude Fable 5, and Sonnet 5 across five categories: PRDs, prototypes, wireframes, debugging, and agentic voice. Sol won by a meaningful margin on my Claire Weighted Index (70% my taste, 30% Terminal Bench 2.1), and I also tested two use cases I can't stop thinking about: building a gamified homework tracking app for my kids in one shot with Codex, and browser automation with Chrome that burned through 500 LinkedIn replies while I did literally nothing.
What you’ll learn:
- How I scored five AI models (including GPT 5.6 Sol, Fable 5, and Sonnet 5) using my “Claire Weighted Index” benchmark across PRDs, prototypes, code, and agentic voice
- The difference between GPT-5.6 Sol (Terra) and Sol for PRD writing
- How Fable’s precision and pedantry made it harder to collaborate with, and the exact moment Sol broke through where Fable got stuck
- Why Sonnet 5 is still my go-to for agentic voice in OpenClaw, even after this whole benchmark
- How I used GPT-5.6 Sol in Codex to build a fully gamified homework tracking app for my kids in one shot
- The video editing use case that saved me hours clipping a talk I gave at Cursor’s event
- How to use Codex plus GPT-5.6 and Chrome for browser automation, and why this is my single most-loved use case right now
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In this episode, I cover:
(00:00) Intro
(01:10) The three GPT-5.6 models: Sol, Terra, Luna
(02:17) Pricing: Sol vs. Fable API costs
(03:24) The How I AI benchmark
(05:03) Claire-weighted Index results
(07:00) Per-task winners: prototypes, PRDs, agentic voice
(11:59) What Claire actually rewards
(13:20) Full-fidelity prototype side-by-sides (Sol vs. Fable)
(17:45) Wireframes
(18:19) Agentic voice
(19:15) Where Sol is better than other models
(23:56) Gamified kids’ homework app, built in one shot
(28:02) Fable’s pedantry problem and how Sol broke through it
(31:49) Two bonus use cases: video editing and browser use
(35:08) Final summary and model recommendations
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Tools referenced:
• GPT 5.6 (Sol, Terra, Luna): https://help.openai.com/en/articles/20001325-a-preview-of-gpt-56-sol-terra-and-luna
• Codex: https://openai.com/codex
• ChatPRD: https://www.chatprd.ai/
• CapCut: https://www.capcut.com/
• Math Academy: https://www.mathacademy.com/
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Other references:
• Cursor event where Claire spoke on the future of PM: https://www.youtube.com/watch?v=4CAFK-rc26A
• ChatPRD blog (where benchmark outputs will be published): https://www.chatprd.ai/
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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
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