Meta’s new ‘Muse Wonder’ model: good for AI agents, bad for design

About this episode

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. 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