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Sonnet 5 review: I ran 64 generations to find out if it's worth it

Anthropic released Sonnet 5, and Claire Vo tested it against four other frontier models using a custom eval harness built with Claude Code. The blind comparison across PRD quality, prototype generation, agentic tasks, and agent personality revealed unexpected results, with model recommendations varying by task.

read2 min views1 publishedJun 30, 2026
Sonnet 5 review: I ran 64 generations to find out if it's worth it
Image: Lennysnewsletter (auto-discovered)

I’ve been testing every major frontier model release since the start of the year, and when Anthropic dropped Sonnet 5, I wanted more than a vibe check. I got tired of one-off tests I couldn’t repeat or compare over time, so I built something better: the How I AI Bench, a repeatable eval harness I constructed live using Claude Code while recording this episode. I ran Sonnet 5 blind against four other frontier models (Sonnet 4.6, Opus 4.8, GPT-5.5, and Gemini 3 Pro) across PRD quality, prototype generation, agentic task completion, and agent personality. The results were not what I expected.

Listen or watch on YouTube, Spotify, or Apple Podcasts

What you’ll learn:

What Anthropic claims Sonnet 5 improves over Sonnet 4.6, and where the benchmark data actually backs that up

How I built the How I AI Bench in under 45 minutes using Claude Code, starting from my own stored session history

Why I combined human vibe scoring (70%) with LLM as judge scoring (30%) instead of trusting either alone

How to set up a local HTML scoring page so you can rate AI outputs on gut feel and export those scores as JSON

Which model I recommend for PRDs, which for complex prototypes, and which for chatting with an agent daily

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In this episode, we cover:

([00:00](https://www.youtube.com/watch?v=yJ-1LB2hF-Q)) Sonnet 5 is out

([01:55](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=115s)) What Anthropic claims

([04:02](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=242s)) Why I’m done with one-off vibe checks

([05:05](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=305s)) Building the How I AI Bench live with Claude Code

([07:42](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=462s)) The scoring system

([10:43](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=643s)) Agent voice eval

([11:57](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=717s)) Quick recap

([13:58](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=838s)) Results: The How I AI index leaderboard

([21:21](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=1281s)) What I’m improving for the next run

([22:16](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=1336s)) Generating a Claire-weighted index

([23:53](https://www.youtube.com/watch?v=yJ-1LB2hF-Q&t=1433s)) Model-by-task recommendations

Tools referenced:

• Claude Sonnet 5: [https://www.anthropic.com/news/claude-sonnet-5](https://www.anthropic.com/news/claude-sonnet-5)

• Claude Opus 4.8: [https://www.anthropic.com/news/claude-opus-4-8](https://www.anthropic.com/news/claude-opus-4-8)

• GPT-5.5 (OpenAI): [https://openai.com/index/introducing-gpt-5-5/](https://openai.com/index/introducing-gpt-5-5/)

• Gemini 3 Pro (Google DeepMind): [https://deepmind.google/models/gemini/pro/](https://deepmind.google/models/gemini/pro/)

• Cursor: [https://www.cursor.com/](https://www.cursor.com/)

Other references:

• SWE-bench Pro (agentic coding benchmark referenced): https://www.swebench.com/

Where to find Claire Vo:

ChatPRD: [https://www.chatprd.ai/](https://www.chatprd.ai/)

Website: [https://clairevo.com/](https://clairevo.com/)

LinkedIn: [https://www.linkedin.com/in/clairevo/](https://www.linkedin.com/in/clairevo/)

Production and marketing by [https://penname.co/](https://penname.co/). For inquiries about sponsoring the podcast, email [[email protected]](/cdn-cgi/l/email-protection).
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