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Japan's Prime Minister briefed her country with wet hair last night. Beijing would have detained the citizen who filmed it. At 10:29 p.m. on Friday, a magnitude 5.6 earthquake struck Japan's Yamanashi Prefecture, registering a maximum seismic intensity of lower 6 in the town of Fujikawaguchiko at the foot of Mount Fuji. By 11:15 p.m. — forty-six minutes later — Prime Minister Sanae Takaichi was standing at the Prime Minister's Office briefing the nation. Crisis management center activated. Director-general-level emergency gathering team convened. Human life first. Information to the public, promptly and accurately. She was also visibly straight out of the bath. Hair still wet. No makeup. Takaichi posted on her own X account a short time later, in plain language: she had come directly from the bath without time to dry her hair or apply makeup, and apologized for her appearance. She did not have to volunteer that detail. She chose to. That choice is the story. Because somewhere about 1,700 miles to the west, operating under the same physics but a very different political philosophy, the first hour after a magnitude 5.6 earthquake would have looked nothing like this. It would not have been spent activating a crisis center, dispatching emergency teams, and putting the head of government in front of cameras to admit she had rushed straight out of the shower. It would have been spent deciding what to tell the public, what to delete, and which citizen with a camera to detain. We know because we have watched it happen. In Wuhan in early 2020, the doctors who tried to warn the world about a novel coronavirus were summoned by police and forced to sign confessions for "spreading rumors." The citizen journalists who filmed the morgues and the sealed apartment doors — Chen Qiushi, Fang Bin, Li Zehua — were disappeared by the state. Fang Bin would later be sentenced to three years in prison; he was held for the duration. In Zhengzhou in July 2021, passengers drowned trapped in a flooded subway tunnel while state propaganda ran headlines about heroic rescue. When BBC correspondent Robin Brant asked the local government how a metro system less than a decade old could leave passengers to die on a platform, the Henan branch of the Communist Youth League posted his whereabouts to its 1.6 million followers and called for people to track him down. Death threats followed within hours. In Hebei in August 2023, when the floodwaters from Typhoon Doksuri had to go somewhere, authorities diverted them away from Beijing and into Zhuozhou — and the Hebei provincial Party Secretary, Ni Yuefeng, publicly declared the province would "serve as a moat for the capital." Videos of the submerged villages disappeared from Chinese social media within hours. And in Sichuan in 2008, after a magnitude 8.0 earthquake killed at least 5,335 schoolchildren in school buildings that collapsed while government offices nearby remained standing — what citizens named "tofu-dreg schoolhouses" — the writer Tan Zuoren tried to compile a list of the dead. He was sentenced to five years in prison. Huang Qi, the activist who tried to help the parents, got three years; in 2019, the Party gave him twelve more on state-secrets charges. He is still inside. The pattern is not a series of accidents. It is a system. In the People's Republic of China, the function of the state in a disaster is not to serve the public. It is to protect the Party from the public. Compare and contrast. In Tokyo on Friday night, the head of government decided that telling the country what she knew, forty-six minutes after the ground stopped shaking, mattered more than how her hair looked. In Beijing under any equivalent scenario, the head of government would not be at a podium for hours, or days. The citizens with cameras would already be on a list. Wet hair is not the real headline. Wet hair is the headline because of what it accidentally exposes: a democracy is a system that runs toward its citizens in the dark. A dictatorship is a system that hides from them. Sanae Takaichi did not need to apologize for her hair. The Chinese Communist Party owes apologies it will never make, to families whose dead it never named. ACI — Aric Chen | Insights

everyone is talking about agent loops, harnesses, and self-evolving agents. but almost no one is talking about the actual hard part: you cannot run a company on one giant agent with every tool, every file, and no accountability. that's not autonomy. that's a fog machine. here's how we're building an agent company OS inside Matrix. — the stack: Workspace Brain → Matrix Runtime Orchestrator → Department Verticals → Department Lead Agents → Worker Agent Pool → Proof / Check-in Loop Matrix is not a chatbot. it's an operating system for autonomous work. — the workspace brain is the company boundary. it gets loaded with the things a real company actually runs on: → product docs → codebase context → chats, files, goals → operating rules → prior runs + examples of good work → approvals, memory, skills this isn't "context." it's the shared operating layer. it knows what the company knows, what it's trying to do, who owns what, what good looks like, and what must be proven before work counts as done. — on top sits the Matrix Runtime. it coordinates wake, cron, department messages, OKR state, permissions, worker dispatch, proof ledger, memory updates. under the runtime, work is organized into departments. a department is not a chat thread. it's a long-running agent with identity, memory, skills, goals, history, tool boundaries, taste, and accountability. Founder Strategy. Product Engineering. Growth. Ops. Research. each one has a lead agent that decides what happens, reads the relevant Memory Skill, breaks work into scoped tasks, and picks the right execution seat. — sometimes that seat is a native Matrix worker. sometimes Codex. sometimes Claude Code. sometimes a browser / computer automation worker. the point is not "one model does everything." the point is: → the right agent → with the right context → inside the right boundary → using the right tools → with a clear definition of done — this is why scoped workers matter. a "do everything" agent is too vague. but: → a release worker with repo context, tests, and approval gates → very good → a Codex worker scoped to one patch and one validation path → very good → a Claude Code worker doing deep repo analysis → very good → a browser worker with a specific flow and proof requirement → very good narrow scope reduces drift. Memory Skill keeps narrow agents from going blind. proof prevents fast output from pretending to be progress. — that is the loop: Workspace Brain → Department Lead → Worker → Artifact → Proof → Check-in → Memory Skill update every cycle, the company gets smarter. that's the real self-evolution. not a single agent rewriting its own prompt in a void — but a whole org compounding through proof. — each workspace is an isolated agent company. its own brain, departments, memory, workers, proof ledger. workspaces can talk when needed. but context should not bleed by default. isolation is not a limitation. it's what makes the system usable. — once a department pattern works, you fork the pattern — not the raw context. you still customize memory, examples, approval gates, tools, voice, definition of done. but you're not starting from zero. you might already have 70% of the OS for that kind of work. — what this actually changes: a small team of strong operators can now run surfaces that used to require entire departments. but only if the agents are actually good. and good agents don't come from connecting more tools. they come from source material, taste, iteration, narrow scope, workflow design, proof, memory, and human judgment. vague agents just create vague output faster. Matrix is our attempt to build the opposite: an agent company OS where autonomous work has structure, memory, ownership, and proof. the loop is the product.

The real constraint on AI isn't chips, or even electricity. It's the intelligence about electricity — the forecasts, dispatch, and hedges that decide whether the grid can serve what AI now demands. Artificial intelligence needs energy intelligence.

HERMES AGENT v0.17.0 JUST SHIPPED. "THE REACH RELEASE." 1,475 COMMITS. 800 PRs. 245 CONTRIBUTORS. HERMES NOW REACHES IMESSAGE, RAFT NETWORK, AND CURSOR'S COMPOSER MODEL. the highlights: @NousResearch iMESSAGE WITHOUT A MAC RELAY Photon Spectrum integration ships native iMessage support. no Mac in a closet. no BlueBubbles bridge. hermes photon login → device code auth → done. Hermes lives in the blue bubbles now. ASYNC SUBAGENTS NO LONGER BLOCK YOUR CHAT delegate_task(background=true) dispatches a subagent that runs in the background. returns a handle immediately. you keep working. result re-enters as a new turn when it finishes. long research dives stop blocking your main session. IMAGE EDITING, NOT JUST GENERATION image_generate now edits source images. "make this logo blue." "remove the background." "turn this sketch into a render." works across every supported image provider. same tool, new mode. CURSOR'S COMPOSER MODEL VIA GROK OAUTH grok-composer-2.5-fast is in the xAI model picker. 200k context window. fast coding model behind Cursor. your Grok subscription. Hermes's agent loop. no separate API key needed. AUTOMATION BLUEPRINTS schedule tasks without learning cron syntax. "daily news briefing at 8am" becomes a form. one blueprint definition renders everywhere: dashboard form, CLI slash command, Telegram chat, docs catalog entry. answer questions, not memorize 0 8 * * *. FULL PROFILE BUILDER IN DASHBOARD build a complete Hermes profile from the browser. pick model. choose skills. attach MCPs. no config.yaml editing. plus unified multi-profile view with global switcher. SKILLS HUB BROWSER REHAUL connected hubs (OpenAI, Anthropic, HuggingFace, NVIDIA). Featured section. full skill previews before install. security scan on each skill. browsing skills is a real browsing experience now. ATOMIC MEMORY OPERATIONS memory tool gained an operations array. batch add/replace/remove edits applied atomically. the model can free space and add entries in ONE call even when individual adds would overflow the budget. memory updates no longer fail mid-edit. CURATOR STOPPED SPENDING TOKENS BY DEFAULT deterministic skill pruning still runs free. LLM-powered consolidation now opt-in only: curator.consolidate: true to enable. routine background curation costs you zero tokens. WHATSAPP BUSINESS CLOUD API official Meta adapter alongside existing Baileys bridge. no QR-scanning bridge process to keep alive. hosted, first-party WhatsApp channel. TELEGRAM RICH MESSAGES (BOT API 10.1) proper rich formatting. cleaner long-message handling. native markup instead of flattened text. on by default. opt-out available. DESKTOP APP IS NOW A DAILY DRIVER rebindable keyboard shortcuts. native OS notifications. live subagent watch-windows streaming activity. composer model selector with per-model presets. automatic RTL/bidi text. resizable VS Code terminal pane. per-thread composer drafts. install ANY VS Code Marketplace theme. RAFT AGENT NETWORK new bundled adapter connects Hermes to raft. build as an external agent. wake-channel bridge. privacy by contract: wake payloads carry metadata only, never message bodies. SECURE DASHBOARD LOGIN every token-required endpoint returns 401 behind OAuth gate. websocket auth uses served dashboard token. public_url override warnings. exposing your dashboard to the network is safer by default. upgrade: hermes update 300+ issues closed. security round included. hermes-agent ecosystem now at 198K GitHub stars.

Here’s everything you need to know about Grok Build’s changelog since release Grok Build is moving fast from a coding CLI into a full terminal-native agent workspace Since launch, it has added or improved plan/review/approve workflows, clean diffs, project-aware context through AGENTS.md, skills, hooks, plugins, MCP servers, parallel subagents, headless mode, ACP support, web/X search, image and video tools, compaction, memory handling, and long-running sessions The biggest upgrade people should not miss is the rendering layer Grok Build can now keep more technical output directly inside the terminal: math, formulas, LaTeX, Mermaid diagrams, ER diagrams, UML/class diagrams, state diagrams, sequence diagrams, tables, media outputs, and richer terminal views That matters a lot for research, ML, simulations, algorithms, database design, infra diagrams, paper implementation, and serious code review The terminal is no longer just where you run commands. It is becoming the place where you understand the work, inspect the logic, review diagrams, and keep moving without constantly copying output into another app The workspace layer is also got much more serious upgrades Agent Dashboard lets you manage multiple coding sessions from one screen, see what is working, idle, blocked, or waiting for input, peek at the latest output, reply inline, and dispatch new work without jumping between sessions The Plugin Marketplace turns Grok Build into an extensible developer environment Plugins can bundle skills, slash commands, agents, hooks, MCP servers, and LSPs. Launch partners include MongoDB, Vercel, Sentry, Chrome DevTools, Cloudflare, and Superpowers. Plugin installs can now resolve directly from registered marketplaces instead of only local paths The latest releases are mostly about making all of this reliable during real work Long responses can resume after network blips. MCP servers recover better after drops or noisy output. Compaction no longer hangs forever. Notifications only fire when user attention is actually needed. Linux clipboard support is stronger. Windows and iTerm rendering are cleaner. Very long sessions can scroll, resume, and quit without falling apart Grok Build is becoming a full terminal-native agent workspace: multi-session, plugin-driven, MCP-connected, diagram-aware, math-capable, media-capable, long-context, and built for developers who actually live in the terminal

Codex现在对我最大的作用，就是在手机上启动家里电脑上的Claude code，然后开启远程控制，方便我在手机上继续coding...🤣🤣🤣 说实话， Claude自己客户端的Dispatch实在是太难用了。。。 ​其实不止 Dispatch，整个客户端做的都挺垃圾的。。。

Surge events put pressure on more than voice traffic. T-Priority prioritizes both voice and responder data to help keep dispatch and coordination systems moving. Because response doesn’t slow down when demand spikes.

Introducing xBubble xBubble is a low-prompt AI agent that unlocks cutting-edge AI productivity with far fewer prompts, much less trial-and-error, and a much lower learning curve. This advantage stems from the following innovations: Bubble Engine: An engine builds task-specific SOPs and probes the limits of AI capabilities for specified tasks. Bubble Pilot: An AI helps users operate AI by dispatching each request to the right SOP. Powerful AI won't require users to learn AI. Read the launch post ↓