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Meta rolled out Muse, a personal AI agent built by Meta Superintelligence Labs that can be messaged through a dedicated app, Muse.ai, or WhatsApp to handle digital chores like sending emails, booking travel, or selling a car. The agent can also make purchases on a user's behalf using single-use virtual card numbers powered by Stripe's Link tool, and is free to try with paid subscriptions needed for heavier use.
Meta AI has released Muse, a new personal AI agent available as an iPhone app and through the web at muse.ai for Mac users. The app lets users customize their agent's name and avatar, and offers free access with weekly usage limits, while paid subscribers get expanded access. Muse is currently limited to the US, with plans to expand to more countries over time.
Meta has introduced a new personal AI agent aimed at everyday users, capable of handling tasks like online shopping and sending emails. The launch is framed as an accessible entry point into agentic AI rather than a developer-focused tool.
Meta introduced Muse, a personal AI assistant for U.S. users that connects to email, calendars, payment apps, and other everyday services to complete tasks like booking travel, paying bills, filling out forms, and making purchases. It arrives powered by Meta's Muse Spark model and uses Link by Stripe for checkout, with Shopify and 1Password integrations planned, while letting users opt in to connect apps individually.
Meta introduced Muse, a personal AI agent that can autonomously handle tasks like online shopping, sending emails, and trip planning by opening browsers, filling out forms, and even negotiating on a user's behalf. The assistant will launch in the US on iOS, Android, and muse.ai, with support for AI glasses planned, and will be free for most users while Meta develops unspecified paid tiers for heavier use.
Meta told staff this week that performance evaluations will no longer be tied to how much they use AI tools, ending a system that had labeled workers 'AI Native,' 'AI First,' or 'AI Enabled' based on chatbot and agent usage. The change comes even as Meta rolls out a new agentic AI tool called Hatch, and employees report their token consumption keeps climbing anyway. The policy shift follows a lawsuit from about two dozen laid-off employees who alleged the AI-usage grading system unfairly penalized workers on health or family leave.
Perplexity has launched a hybrid compute feature for its Computer agentic platform that splits AI tasks between cloud-based frontier models and smaller open-weight models running locally on Apple silicon Macs. Sensitive data is automatically routed to the on-device model via a locally-run 'Privacy Gate' classifier that detects personal information before anything reaches the cloud, without interrupting the task or losing context. The feature launches today for opted-in enterprise customers plus Pro and Max subscribers on Macs running macOS 15 or later.
OpenClaw, the viral open-source AI agent that autonomously executes tasks across apps like WhatsApp, Slack and Discord, has released version 2.0. The company calls it the largest update in the project's history, adding new features, expanded capabilities and bug fixes since its chaotic rise to fame earlier this year.
OpenClaw released version 2026.8.1, branded as 2.0, marking its biggest update since launching last November. The overhaul began as a plan to simplify installation and rebuild the browser client but expanded into a full codebase rework, involving 933 contributors and over 16,000 merged pull requests.
A developer released Talos, version 0.15.1-alpha, an MIT-licensed AI agent that pairs a sandboxed Claude-based worker with real shell access for building, testing, and browsing tasks. Every action the agent attempts is checked by a separate deterministic security kernel that authorizes each tool call individually, tying it to exact arguments and letting it run only once within a thirty-second window.
OpenAI is said to be developing a persistent AI agent capable of running continuously rather than only responding to single prompts. The agent would maintain ongoing awareness of tasks and context over time, moving beyond the transactional chat-based model most assistants use today.
An analysis presented by Gravitee argues that the real danger in enterprise AI deployments isn't individual autonomous agents but the tangled web of connections between fleets of agents calling APIs, other agents, and applications never designed for machine decision-makers. As organizations add more agents, the number of possible interaction paths grows far faster than agent count, making systems opaque and nearly impossible to govern with simple approval checklists.