标签：#Go

Enterprise AI's real risk isn't autonomous agents. It's the complexity between them. Executive Briefing — September 2026 When enterprises deploy fleets of AI agents instead of single systems, the real danger is not a rogue agent. It is the emergent complexity of their interactions — a web of cascading calls, forgotten permissions, and accountability gaps that no checklist can fix. 1. The problem nobody sees coming Enterprises do not deploy one agent and watch it run. They deploy fleets: support bots, retrieval agents, orchestration layers, each calling APIs, delegating to other agents, reaching into systems that were never designed for machine decision-makers. The failure mode that should keep you up at night is not a single agent doing something bad. It is a hundred agents doing exactly what they were built to do, all at once, in combinations nobody designed for. Complexity does not grow linearly with agent count. Add a second agent and you add one connection. Add a tenth and you potentially add dozens, because any agent might call any other, and each call can trigger another somewhere else. A support ticket that used to touch one system might now pass through four agents before a human ever sees it. Every handoff is an undocumented decision point. Most enterprise AI programs stall when the humans responsible lose the thread. Ask a security team which agents can reach which systems, and you get silence. Ask which agent triggered which downstream action three hops ago. More silence. 2. Why checklists fail The instinct is to treat this like a compliance checklist. Approve the agent. Log the agent. Move on. But a checklist checks a single point in time. Complexity runs across a chain, and you cannot govern a chain with a stack of one-time approvals any more than you can call a diet successful because you had a vegetable once. Two failure modes dominate. Permissions creep. Somebody builds an agent to summarize support tickets and grants it broad API access because scop

Zoph, who co-founded Thinking Machines Lab alongside Mira Murati and also served as the startup's CTO, led a brief stint at OpenAI and is now at Google.

Google's AI note-taking app, Gemini Notebook, can now pull information from the books you've purchased. The new "Expert Intelligence" feature allows you to bring titles from Google Play Books directly into Gemini Notebook, which means you can ask questions about the material, as well as generate plans, infographics, AI podcasts, and more based on their […]

Google will start policing memory-hungry Android apps as a direct response to the RAM crisis. Spotted by TechCrunch, the company yesterday published a memo addressing the Play Store's role in enforcing new memory-usage restrictions. The post emphasizes the importance of meeting new memory usage limits for apps, in order "to help developers navigate industry-wide hardware […]

Your coding agent talks to a model provider over HTTPS. That connection is a straight line: the agent asks, the provider answers, the answer lands in your editor. Nothing in the middle looks at what came back. For most of what an agent produces, that's fine. For the rest of it — the query built by string concatenation, the API key the model helpfully echoed back into a code sample, the eval() on user input — you find out later, in review, or in a scanner run, or never. This is a walkthrough of putting a policy layer in that line: a local proxy your agent points at instead of the provider, which inspects the response stream and decides allow , redact , or block before the text reaches you. I'll use Cencurity Engine because it's the one I build, it's Apache-2.0, and it runs entirely on your machine. The pattern generalises — if you're building your own gateway, the steps below are still the shape of the problem. What you need first Go installed (the engine is a Go binary you run from source) An API key for whatever provider your agent already uses An agent or IDE that lets you override the API base URL That last one is the real prerequisite. If your tool hardcodes the provider endpoint, none of this applies to it. Most don't: Roo Code, Continue, Claude Code and Gemini CLI all expose a base URL, and anything reading OPENAI_API_BASE will work too. Step 1: Start the gateway Clone the repo, open a terminal in it, and run: go run ./cmd/cast serve \ --listen :8080 \ --upstream https://api.openai.com \ --policy ./cast.rules.example.json Three flags, and each one is doing something you should understand before moving on: --listen is where the gateway accepts traffic. Local only. --upstream is your real provider base URL. Swap it for https://api.anthropic.com , https://api.deepseek.com , https://api.x.ai — whatever you actually use. --policy is the rule file. cast.rules.example.json ships in the repo and is a working starter set, not a placeholder. Note what is not in that com

The ATF is the latest federal government agency in recent years to notify Congress of a "major incident" involving its cybersecurity.

Some of the world's largest tech companies and AI startups have come together to decry the current state of cybersecurity and to advertise a new solution that they say can ward off a new generation of cyber threats.

Google AI Mode is getting a flight price tracker, hotel booking and a way to view the cost in miles or points.

The updates indicate that Google is looking position to AI Mode as an AI travel agent of sorts, as it's moving beyond simply helping users find information to actually handling parts of the trip-planning and booking process itself.

Google Cloud has introduced AI-powered Database Operations Agents, featuring an Onboarding Agent that streamlines database setup and an Observability Agent that helps automate troubleshooting, performance optimization, and tuning. Integrated with Gemini Cloud Assist, these agents support multiple database services, including AlloyDB, Bigtable, and Spanner. By Sergio De Simone

The latest special-edition of Google's Fitbit Air is inspired by the Pokémon Sleep game, with a "Sleepy Blue" band emblazoned with a snoozing Pikachu. It's not exactly Snorlax blue, but matches the classic blue and gold of a Pokémon card pretty closely. The special-edition is available to preorder now for $129 and starts shipping September […]

Google is setting new memory-use limits for Android apps as AI data centers contribute to hardware shortages that could leave lower-cost phones with less memory.

Meta might be on the hook for $17.1 billion and a host of app changes under a new kids safety settlement, but it's already spinning the deal to its advantage. After years of being the national punching bag for social media harms, Meta has reached a settlement with 47 US states and several districts and […]

Encrypted Client Hello rolls out on Android 17 to make the web more secure.

GitHub热门项目 | Help AI coding agents write modern Go | Stars: 1,885 | 314 stars today | 语言: Go

You're probably using Android System Intelligence more than you realize -- especially if your phone is a Google Pixel.

OpenAI has more than 100 million weekly active ChatGPT users in India, a huge chunk of whom are on the free or the lower-priced Go tiers.

OpenAI disrupted a social engineering group from Cambodia that used ChatGPT. Its scope is impressive: The network simultaneously conducted multiple types of scams, often blending elements from different schemes. For instance, operators used dating personas to build trust before introducing fraudulent investment opportunities involving cryptocurrencies and spot gold trading. Other users engaged in lengthy romantic conversations with targets using fictitious identities, posed as representatives of online gambling platforms offering fake bonuses and winnings, or impersonated law enforcement agencies to tell targets they needed to pay fines for committing serious criminal offenses...

Every workflow builder I have used opens the same way: a blank canvas and a palette of nodes. Zapier, n8n, Make - all of them assume you already know what you want, already decomposed into steps, before the tool is any use to you. Most people don't. They know the chore . "I keep forgetting to check the weather before I bike in." The gap between knowing the chore and knowing the DAG is precisely the work these tools leave you to do alone, and I think it is why most people who try one never build a second automation. So I built Weaver, which inverts it. Weaver interviews you about the chore, one question at a time, until it actually understands the goal. Then it designs the workflow, validates it, deploys it, and runs it. The canvas is an output rather than an input. This post is about the parts that did not go to plan, because those are the parts worth reading. The interview is the whole product Three rules, and they are harder than they look: One question per turn. Never three bundled into a paragraph. Never invent a value the person has not given you. No quietly assumed recipient, city, or time. A correction updates one detail. Say "actually, Mondays" halfway through and it changes that and keeps going, instead of restarting the interview. That third one is the one people notice. Restarting an interview because the user corrected themselves is the single fastest way to make software feel like it is not listening. Only once it restates the whole task in plain language and you confirm does it save the intent and hand off to a separate Designer Agent. Two agents, deliberately not one The Conversation Agent and the Designer Agent are different models with different prompts and no shared state beyond a saved intent. That is a design decision, not an accident of implementation. Understanding a person and designing a system are different skills with different failure modes. Collapsing them into one prompt makes both worse: the interviewer starts proposing architecture hal

The European Union's Roam Like at Home regime now extends to Moldova and Ukraine, broadening the area where travellers can use mobile calls, SMS and data at their domestic price. For companies whose staff travel, work in the field or coordinate operations across these markets, the change can make mobile spending more predictable and reduce a familiar source of cross-border friction. The extension was approved by the Council of the EU in July 2025 for application from 2026. The Council's official announcement on the roaming extension confirms that Moldova and Ukraine were set to join the EU roaming area from 1 January 2026. Follow-up EU updates recorded Ukraine's formal accession in Kyiv on 12 January 2026. In practical terms, a customer from an EU country, Moldova or Ukraine can use their domestic mobile plan while roaming in the other participating areas, rather than facing a separate retail roaming tariff. The arrangement is not a blanket promise of unlimited use abroad, however. It operates under the established Roam Like at Home framework, including fair-use policies, sustainability derogations and wholesale roaming charges. What the extension changes for cross-border work For a travelling employee, a mobile connection is part of the working toolkit. Calls with customers, two-factor authentication messages, map and logistics apps, messaging platforms and cloud services can all rely on roaming data. Bringing Moldova and Ukraine into the same roaming area gives businesses a clearer basis for planning those routine costs when staff move between the EU and either country. The change also matters for service consistency. EU communications around the extension stress that roaming customers should receive the same quality of service available at home, including access to technologies such as 4G where those are available under the domestic service. That principle is important for work that depends on stable mobile data, although real-world performance will still depend