Meta’s new ‘Muse Wonder’ model: good for AI agents, bad for design
Watch now (24 mins) | 🎙️Meta launched Muse Wonder with claims of frontier agentic performance, so I ran it headlessly through Claude Code against nearly 20 tasks to find out if any of it is true
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Meta’s new ‘Muse Wonder’ model: good for AI agents, bad for design
🎙️Meta launched Muse Wonder with claims of frontier agentic performance, so I ran it headlessly through Claude Code against nearly 20 tasks to find out if any of it is true
Claire Vo
Oct 14, 2026
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Transcript
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.
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,
Spotify
, or
Apple Podcasts
What you’ll learn:
Why Meta’s “personal and professional agent” framing mostly holds up, and where it doesn’t
What active focus mode actually does on long-running tasks, and whether it’s real
The three agentic tasks where Muse ranked first, and why those categories matter
What Muse’s design output actually looks like (it’s not good)
How it compares to Sonnet on voice assistant tasks
Where Muse lands on SVG and short-form video versus Opus 5.5, Astra, and Fable
Whether I’m actually putting Muse into any of my agent workflows
Brought to you by:
DX
—Engineering intelligence for the AI era
Jira Product Discovery
—Prioritize with insights, build with confidence
In this episode, we cover:
(
00:00
) Intro and what Muse Wonder is
(
01:19
) Meta’s frontier capability claims
(
04:36
) Muse code
(
06:06
) Benchmark overview and how the How I AI bench works
(
07:51
) Overall results and TL;DR verdict
(
11:53
) Agentic tasks
(
13:36
) Email writing and voice assistant performance
(
14:35
) Where Muse falls short
(
18:28
) SVG illustration results
(
19:33
) Short-form video editing
(
21:18
) Fast on one-shot work, slow on agent tasks
(
22:15
) Final verdict and where I’ll use Muse Wonder next
Tools referenced:
• Meta Muse Wonder / Muse Wonder Full:
https://research.meta.ai/blog/muse-wonder
• Muse Code:
https://developer.meta.com/ai/lp/muse-code
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]
.
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How I AI
How I AI, hosted by Claire Vo, is for anyone wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will share a specific, practical, and impactful way they’ve learned to use AI in their work or life. Expect 30-minute episodes, live screen sharing, and tips/tricks/workflows you can copy immediately. If you want to demystify AI and learn the skills you need to thrive in this new world, this podcast is for you.
How I AI, hosted by Claire Vo, is for anyone wondering how to actually use these magical new tools to improve the quality and efficiency of their work. In each episode, guests will share a specific, practical, and impactful way they’ve learned to use AI in their work or life. Expect 30-minute episodes, live screen sharing, and tips/tricks/workflows you can copy immediately. If you want to demystify AI and learn the skills you need to thrive in this new world, this podcast is for you.
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