Muse: The First Personal AI Agent Built for Everyone
Today, Meta is introducing Muse, a secure, private personal AI agent that proactively helps with people’s goals and suggests ideas. Because personal agents need a new kind of secure computer, Muse runs on Muse Secure VM, a dedicated, virtual machine (VM) that houses both the agent and a person’s data. Muse is designed around the way people already communicate, so talking to it works just like messaging another person, in the Muse app or directly in WhatsApp.
- ▪Today, Meta is introducing Muse, a secure, private personal AI agent that proactively helps with people’s goals and suggests ideas.
- ▪Because personal agents need a new kind of secure computer, Muse runs on Muse Secure VM, a dedicated, virtual machine (VM) that houses both the agent and a person’s data.
- ▪Muse is designed around the way people already communicate, so talking to it works just like messaging another person, in the Muse app or directly in WhatsApp.
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,073 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Meta Newsroom |
| Canonical URL | https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/ |
| Publication time | Tue, 22 Sep 2026 23:17:32 +0000 |
| Retrieval time | 2026-09-22T23:24:29.924Z |
| Last seen | 2026-09-22T23:24:29.924Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | Y_xRG8oqm64I · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Today, Meta is introducing Muse, a secure, private personal AI agent that proactively helps with people’s goals and suggests ideas. Because personal agents need a new kind of secure computer, Muse runs on Muse Secure VM, a dedicated, virtual machine (VM) that houses both the agent and a person’s data. Muse is designed around the way people already communicate, so talking to it works just like messaging another person, in the Muse app or directly in WhatsApp. It’s simple to use. People just tell Muse what needs to get done, and it takes action, powered by Muse Spark, Meta’s most capable model to date, built for real-world agentic work like this. How It Works Unlike other agents, Muse was built to work for billions of people worldwide, so there’s no learning curve.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Meta Newsroom.
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