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The UK’s energy regulator is using a variety of tricks to keep speculative data center projects from plugging into the power grid. The country’s AI ambitions hang in the balance.

You can build a working agent mesh with QUIC transport, encrypted messaging, and decentralized coordination. Five processes can reinforce independent conclusions and let unsupported signals decay. The mesh works. Then you try to introduce it to another agent and discover you have no standard way to ask what the swarm can do. No retained task to retrieve after an internal signal expires. No interoperable progress stream. No cancellation contract. No artifact another framework would understand. SMESH is a Rust-based decentralized agent framework that hit this boundary. The author had built a society with no border crossing. The solution was Google's Agent2Agent (A2A) protocol, announced in April 2025 and moved under Linux Foundation governance in June 2025. A2A provides the missing public contract: a way for agents built by different vendors to discover one another, exchange messages, and collaborate without sharing private memory, tools, or internal plans. The Cold-Start Problem in Agent Meshes Traditional service meshes solve discovery with a central registry. Kubernetes has etcd. Consul has its catalog. Envoy has xDS. You register your service, get a DNS name or IP, and other services find you. This works because services are relatively static and the registry is the source of truth. Agent meshes are different. Agents are ephemeral, context-dependent, and often spawned on demand. They need to: Discover peers without a central registry Exchange capability metadata at runtime Negotiate protocols without pre-shared configuration Maintain security boundaries during introduction The coordination primitives (message passing, consensus, signal decay) assume agents already know about each other. Discovery is the layer below coordination. SMESH had the top layer working but no way to bootstrap the bottom layer without manual wiring. What A2A Provides A2A is not a coordination protocol. It is an introduction protocol. The spec defines: Discovery handshake : How agents announ

Keep the beams standing. Replace what they carry. — The 36 Stratagems, Replace the beams with rotten...

Nvidia's predicting it will pull in $108 billion in revenue within just a few months. It wouldn't be the first company to rake in over $100 billion in quarterly revenue - Amazon, Apple, and Alphabet have repeatedly reached the milestone. Nvidia said in its latest earnings report that it brought in a record $96.2 billion […]

Child safety groups and former Meta employees welcome proposed changes to how the company’s platforms will work for teens. They also think states should have demanded more.

Introducing AI Disclosure on DEV: Tools for Nuance, Clarity, and Better Feeds Author leads by example using the new tag Ben Halpern Ben Halpern Ben Halpern Follow for The DEV Team Aug 26 Introducing AI Disclosure on DEV: Tools for Nuance, Clarity, and Better Feeds # showdev # announcements # ai # community 49 reactions 3 comments 3 min read

Judge hasn't ruled on X Corp’s preliminary injunction, but Operation Bluebird plows ahead

Two weeks ago I counted 204 guards in my repos and found that 89 % had never been shown they can...

The bishops' snub comes as the state continues to attack vaccines.

The AI giant acknowledges that it could have done far more to prevent its AI agents from going rogue. But it still fails to explain why it didn't see this fiasco coming.

Claude Code is amazing. It feels like cheating in the best way until it doesn't. The first time I dropped a vague comment and it gave me a fully working component, I was hooked. But somewhere along the way, I realized something weird was happening: I was coding less... and thinking less. Let’s talk about that. The Tools Got Better, But We Got Lazier In 2022, you still had to know stuff . Now? You just prompt your way through half the job. And sure, productivity skyrocketed. Ship faster, write fewer tests, scaffold full APIs in a couple of minutes. But here’s the tradeoff no one likes to talk about: we’re outsourcing thinking . Not tasks. Not code. Thinking. I've seen teammates slowly stop debugging on their own. They just throw the stack trace into Claude. I’ve seen people stop learning the fundamentals of async behavior or memory handling because “Claude will tell me.” Cool. Until Claude gives you a bad answer and you don’t realize it because you stopped building your intuition. The Industry’s Not the Same The layoffs? Brutal. And the worst part isn’t just losing a job it’s realizing you didn’t build portable skills . Because if Claude wrote all your code at your last job, what exactly did you learn? When companies trimmed down, they didn’t just cut bodies. They cut noise. They kept the people who could solve problems , not the ones who could Google fast or write perfect prompts. So ask yourself: if Claude disappeared tomorrow, could you still contribute? Using AI ≠ Being a Great Engineer I’m not anti-AI. I use Claude. I use Cursor. I use Copilot. But I don’t depend on them. There’s a difference between boosting productivity and becoming a prompt monkey. The first one makes you valuable. The second one… doesn’t. Let’s get real: code was never the point. It was always about solving problems, navigating ambiguity, simplifying complex systems, designing clean architecture. None of that goes away with AI. In fact, it becomes more important. The Skills You’ll Regret Not

Beijing’s endlessly delightful Robot Games featured tons of impressive stunts. But the most mind-blowing tricks challenged the humanoid’s brain, not its brawn.

China’s hacking campaign targeted NASA, the Federal Reserve, the US Senate, the Justice Department, and more, according to the DOJ.

In addition to sending billions of dollars to states, Meta will make substantive changes to its platforms as part of a landmark settlement.

SoundCloud has launched a new beta feature that allows artists on the audio streaming platform to sell music directly from their profiles, instead of diverting fans to purchase from third-party services like Bandcamp and Beatport. The feature aims to give listeners a better way to support the musicians behind their favorite songs, because SoundCloud isn't […]

Robot bodies are waiting for their AI brains to catch up.

GitHub热门项目 | 日報管理リポジトリ | Stars: 133 | 13 stars today | 语言: Rust

GitHub热门项目 | Mission control for your AI agents | Stars: 406 | 108 stars today | 语言: Rust

The startup came out of stealth with $6 million in seed funding and a plan to use LLMs and cybersecurity know-how to make AI queries coherent.

A solid observability setup usually comes down to three pieces working together: something that collects metrics, something that exposes system-level metrics, and something that visualizes it all. Here's what each one does and how to install them. The Theory: How This All Fits Together Before installing anything, it helps to understand the model, because it's a bit different from how logging or alerting tools usually work. Pull, not push. Most people's first instinct is "the app should send its metrics somewhere." Prometheus flips that around — it pulls metrics on a timer instead. Every target (a machine, a service, an app) exposes a simple HTTP endpoint, usually /metrics , that just returns plain text numbers. Prometheus visits that endpoint every N seconds (the "scrape interval") and saves whatever it finds, with a timestamp attached. Nothing gets pushed to Prometheus — Prometheus goes and asks. This means for anything to show up in Prometheus, it has to satisfy one requirement: something has to expose a /metrics endpoint Prometheus can reach. That's the whole game. Everything else in this stack exists to satisfy that one requirement or to make the data useful afterward. Why Node Exporter exists. Your operating system doesn't naturally speak Prometheus's language — it doesn't expose CPU/memory/disk stats as a /metrics endpoint by default. Node Exporter's only job is to read stats the OS already tracks (via /proc and /sys on Linux) and republish them in the text format Prometheus expects, on port 9100. It's a translator, not a monitoring tool by itself — it collects nothing, decides nothing, alerts on nothing. It just answers "what does this machine look like right now?" whenever asked. Why Prometheus itself is separate. Prometheus doesn't know anything about CPUs or memory — it has no idea what it's scraping. It just knows: "go hit this list of URLs on a schedule, and remember what comes back." The intelligence is in the config (which targets to scrape, how often)