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Earlier today NEAR Intents services were stopped after a security incident was detected. The incident was caused by a bug in the Omni deposit and withdrawal infrastructure interaction with NEAR Intents smart contract. The preliminary report indicates the total loss of approximately $3.8M. These funds will be compensated in full. The contract-side vulnerability has been patched. The operations of the NEAR Intents and near(.)com are expected to resume within 1h. Deposits and withdrawals on the following networks will remain unavailable for an additional ~12 hours while fixes to the Omni infrastructure are completed: BSC, Polygon, TON, Optimism, Avalanche, Stellar, Monad, LayerX, Adi, Scroll and Plasma. In case users hold any assets from these chains inside NEAR Intents (for example, in HOT wallet or on near(.)com), they will be able to swap them into other assets once NEAR Intents is back up (in ~1h). The incident has been reported to law enforcement, and we are working with security and blockchain analytics partners to trace the funds and pursue recovery. A detailed report will be shared publicly in the following days.

OpenAI Dots is insane for building a 24/7 AI company... I mapped the whole OpenAI Dots architecture into one paper: agents, models, tools, memory, delegation, guardrails and the revenue layer. Here are the 10 steps: step 1 → stop treating Dots like a chatbot. each Dot runs in a persistent cloud environment with its own browser, terminal, files, memory and scheduled execution. close the laptop and the workflow keeps moving step 2 → hire by responsibility. give every Dot one clear domain, dedicated sources, a working style, an approval boundary and a trigger. a "general helper" has no role, only undefined context step 3 → make one Dot the orchestrator. you give it the objective, it decomposes the work, delegates to specialized agents, checks their outputs and merges everything into one deliverable step 4 → stop being the courier between agents. with isolated delegation, each worker gets only the context and tools it needs, executes in its own environment, then returns a structured result to the orchestrator step 5 → connect the real business stack: cloud browser sessions, Slack, Microsoft Teams, Google Workspace, internal dashboards and APIs. a Dot without tools is still just a conversational layer step 6 → put the company on a clock. recurring routines and event triggers turn one-off tasks into persistent operations. research, monitoring, reporting and pipeline checks can run while nobody is online step 7 → automate the reversible, gate the irreversible. let agents read, research, analyze and draft autonomously, but require human approval before messages send, money moves, records change or production code ships step 8 → route intelligence by cost. keep the strongest model on orchestration, conflict resolution and final audits, and let cheaper high-context models handle background research, classification and repetitive execution step 9 → give the company shared memory. project specs, approved claims, pricing, decisions and requirements live in one persistent workspace, so every agent works from the same source of truth instead of rebuilding context from old chats step 10 → connect the loop to revenue. research finds the signal, outreach creates the opportunity, execution moves the work forward, analytics measures the result and monitoring discovers the next action AI stops being something you open when you need an answer. It becomes an operating layer that keeps economically useful work moving after you log off. Copy the complete OpenAI Dots architecture blueprint, then read the full roadmap below ↓

这是纯宝藏：20 个 AI agent 技能，覆盖从构建到上线的完整闭环。 规格、架构、agent、后端、数据、UI、测试、安全、分析、交付。 定义任务 1. bmad-spec 把想法变成结构化的规格。 2. domain-modeling 为系统里的核心概念和关系建模。 3. codebase-design 规划代码库该怎么组织。 4. google-agents-cli-workflow 用 Google Agents CLI 搭建 agent 工作流。 5. prompt-optimizer 改进和打磨 prompt。 构建系统 6. google-agents-cli-adk-code 用 Google 的工具构建 agent 代码。 7. mastra 构建 AI agent 系统的技能。 8. typesafe-ai 用更强的类型安全构建 AI 工作流。 9. fastify-best-practices Fastify 后端的更好模式。 10. neon-postgres 使用 Neon + Postgres。 让它可用 11. prisma-database-setup 用 Prisma 搭建数据库层。 12. clerk-orgs 加入组织与认证工作流。 13. emil-design-eng 改进产品设计和前端执行。 14. review-animations 审查并改进 UI 动画。 15. remotion-best-practices 构建更好的程序化视频工作流。 验证真实效果 16. playwright-cli 测试真实浏览器路径。 17. semgrep 扫描代码库的安全问题。 18. sentry-fix-issues 发现并修复生产环境问题。 19. instrument-product-analytics 追踪用户在产品里实际做了什么。 20. email-best-practices 改进产品邮件流程。 这个闭环： 想法 → 规格 → 架构 → 构建 → 浏览器测试 → 捕获失败 → 衡量用户 → 改进下一个版本。 找出你项目里最大的瓶颈，先装上能攻克它的那个技能。 收藏这条，为你的产品建一个第二大脑。

BCH-1 Alumni Update 🚀: @CashMintLabs , AI Agents Thirty days ago we wrote about CashMint's AI Agents on the eve of its launch: a Hackcelerator runner-up, audited contracts, and a plan to give an AI agent its own economy. The month since has been a case study in what that actually looks like. The agent works for a living. Minty's job board on shows a public ledger of paid assignments: sponsored coverage, analytics charts, research tasks, each priced in BCH, each delivered on-chain. Gig number 73 went through last week. The agents page now lists a second hire in waiting, CashGuard, an AI that audits CashScript contracts. An AI labor market, small but real. The token worked as designed. MINTY graduated its bonding curve in four hours. It trades on Cauldron and Guanaco, climbed to a top-ten Cauldron ranking in nine days, and 85% of its liquidity is burned. Revenue share, fair launch, no presale, no insider allocation. What we said on September 14 holds: agent economies need cash-like fees to be a business model. Thirty days in, one is running. The pipeline is active. More updates as teams hit milestones. $BCH

TRON joined @CoinDesk Policy & Regulation 2026 in Washington, D.C. as a Gold Sponsor. 🇺🇸 The event focused on the conversations shaping digital asset regulation, from transparency and on-chain analytics to collaboration across the public and private sectors.

𝕏 Ads just became agent-native... and this is a very powerful upgrade With the new 𝕏 Ads MCP, you can now connect Grok, Grok Build, Claude Code or other AI agents directly to your 𝕏 Ads account and manage campaigns through normal conversation You can literally ask: “How are my ads performing?” And the agent pulls real campaign data, analyzes the results, and tells you what’s working But it goes much further than analytics The AI can: • Create and manage campaigns • Search interests and locations for targeting • Add or remove targeting • Create ad posts • Promote existing posts • Check campaign performance and reach • Update and activate campaigns There are 23 𝕏 Ads tools available through the MCP And the safety design is actually smart: New campaigns and line items are created PAUSED by default, so the AI cannot start spending money until you explicitly activate them The agent can even chain the entire workflow itself: Your request → account → budget → campaign → targeting → ad This is where advertising is heading Instead of living inside Ads Manager, you just tell your AI what you want to achieve and the agent runs the campaign for you

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE Content was never a talent problem. It's a headcount problem. One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas. Here's what one of these setups actually looks like. A Chief of Staff sits in the middle and routes every task. Nothing lands on the human. → Researcher tracks what's actually moving and pulls real sources instead of guesswork → Writer turns that research into finished copy, ready to review → Visualiser gets fed a few reference visuals once, then ships everything in that style → Analyst reads the numbers and tells the rest of the team what worked → Scheduler owns timing and holds the queue → Publisher ships it The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory. So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle. You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern. And that's the real shift. Nobody needs AI to tell them what to post. They need it to delete the 40 steps between the idea and the post. Everyone has a backlog of things they've meant to make for months. This is what starts clearing it. Full breakdown of the setup in the article below ↓

推荐给产品经理们的「PM Skills Marketplace」 开源作者 @PawelHuryn 把经典产品管理方法论封装成 AI 可调用的「68 Skills + 42 Commands + 9 Plugins」，让 Codex、Cursor、Claude Code、WorkBuddy 等变成"懂 PM 方法论的工作伙伴"。 # 三层架构、九个插件：Skills -> Commands -> Plugins 1. pm-product-discovery（13 Skills / 5 Commands） 创意发散、假设识别与排序、OST 机会树、用户访谈脚本、实验设计 2. pm-product-strategy（12 / 5） 战略画布、愿景、价值主张、Lean/BMC 画布、定价、SWOT/PESTLE/波特五力/Ansoff 3. pm-execution（16 / 11） 日常执行核心：PRD、OKR、成果导向路线图、冲刺/复盘、发布说明、利益相关者地图、用户故事、9 种优先级框架、红队压力测试 4. pm-market-research（7 / 3） 用户画像、细分、旅程地图、TAM/SAM/SOM、竞品分析、情感分析 5. pm-data-analytics（3 / 3） 自然语言转 SQL、同期群分析、A/B 测试统计显著性分析 6. pm-go-to-market（6 / 3） 滩头市场、ICP、增长飞轮、GTM 模式、竞品作战卡 7. pm-marketing-growth（5 / 2） 定位、价值主张、命名、北极星指标 8. pm-toolkit（4 / 5） 简历评审、NDA/隐私政策起草、校对 9. pm-ai-shipping（2 / 5） 最有特色的一个：为" vibe-coded 代码"补齐可审查性——逆向生成系统文档、静态安全/性能审计、测试覆盖映射，专门发现"文档说的与代码实际做的之间的差距"这类通用扫描器漏掉的问题

Big news: Qwen3.8-Max by @Alibaba_Qwen just landed at #4# on the Frontend Code Arena leaderboard with a score of 1,668! With 1,668 points, Qwen3.8-Max is trailing only Claude Opus 5 (Max) with 1,705 pts and Kimi K3 (Max) with 1,676 pts, on par with Claude Opus 5 (High) with 1669 pts. It also ranks high across all domains: #2# in Consumer Product #3# in Brand & Marketing, Reference-based design, Gaming, and Content Creation Tools #4# in Data & Analytics #5# Simulations Dig into the thread for more details and to see how it also performs on real-world tasks in the Text Arena. Congrats to @Alibaba_Qwen on this huge release!