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AI won't replace people. People using AI will replace people who don't. 真正拉开差距的，非 AI 本身，而是每天都在用 AI 的人。 #AI# #ChatGPT# #AIAutomation# #AITools# #Productivity# #FutureOfWork# #WorkSmart# #Automation# #DigitalSkills# #PersonalGrowth# #BuildInPublic# #OnlineBusiness# #CreatorEconomy# #TechTrends# #Web3# #Cryptocurrency#

一个开发者使用 Claude Code 每月为 47 个单独的小企业客户赚取约 400 美元，每个客户。这种系统遍历 Google Maps，自动识别并转化没有网站的本地商户，无需人工干预，从传统外包模式中平了中间门槛。是否能扩展到更多细分服务领域？ #AI# #Automation# #BusinessGrowth#

O’KEEFE INFILTRATES NJ ANTIFA: Inside “NJ BURN” — Rutgers University Director, T-Mobile AI Leaders, OpenAI /ChatGPT Engineer, Reverend From Princeton Theological Seminary, and ACLU Board Member Discuss Port Newark–Elizabeth Blockade Riot, Road Spikes, Tire-Slashing of New Jersey Police Vehicles, “Ukrainian-Style” Protest Tactics, and Celebrating Charlie Kirk’s Murder. NJ ANTIFA INDIVIDUALS IDENTIFIED: • Alexyss P. - New Jersey Coalition Against Sexual Assault Community Council Member @NJ_CASA • Jim Keady @JWKeady -  Former New Jersey Democratic Candidate • Woojin Ko - OpenAI Research Engineer @OpenAI • Beleckecom Moffouk - T-Mobile AI Automation Expert @TMobile • Zainab Tanvir - Imaging Director at Rutgers University @RutgersU • Amanda Marie Dominguez - Rutgers University PHD Student in Education @RutgersU • Aditi Rao @aditilrao - Princeton University Classics @Princeton • Shannon Smythe - Princeton Theological Seminary Field Education Director @Princeton • Cres Vellucci @CresVellucci - National Lawyers Guild Co-Founder/Co-Member & ACLU Board Of Directors  @NLGnews @ACLU • Celine Semaan @celinecelines - Co-Founder Slow Factory Labs @theslowfactory

This is insane. A college dropout from Massachusetts Institute of Technology reportedly made $297,000 using a simple Bitcoin arbitrage strategy. He noticed BTC was selling for thousands more on overseas exchanges due to local demand. So he would: • Buy BTC cheap on U.S. exchanges • Transfer it overseas • Sell it higher instantly • Repeat daily Once he automated the process with bots, the profits scaled fast. No meme coins. No gambling. Just spotting inefficiencies before everyone else. The biggest money is made where attention is low. I have a complete arbitration course. Action items: Learn AI + automation Study market inefficiencies Build systems, not hype Test ideas daily Follow me @mikezillionaire Comment “AI” and like + share to get the course👇

So few people are actually taking advantage of AI to automate boring work. I sat down with @bentossell to chat about how to close the gap in the world of AI automation using low/no code tools like Zapier and others. Happy automating : )

A List of Robotics Stocks: Humanoids $TSLA Tesla $XPEV Xpeng $AGLT Agility $XIACF Xiaomi $HYMTF Hyundai Sensors $VPG Vishay Precision $OUST Ouster $ARBE Arbe Robotics $MVIS MicroVision $AUR Aurora $CGNX Cognex $INVZ Innoviz Chips $NVDA Nvidia $AMBQ Ambiq $AMBA Ambarella $INDI indie Logistics $AMZN Amazon $SYM Symbotic Deep Sea Robotics $KRKNF Kraken Robotics $OII Oceaneering Healthcare Robotics $ISRG Intuitive Surgical $SYK Stryker $MDT Medtronic $PRCT PROCEPT Industrial Robotics $HON Honeywell $TER Teradyne $LECO Lincoln Electric Robotics Automation $PEGA Pegasystems $ROK Rockwell Automation $ABBN ABB $ZBRA Zebra Technologies $CGNX Cognex $PATH UiPath Defense Robotics $AVAV AeroVironment $KTOS Kratos $LMT Lockheed Martin $NOC Northrop Grumman $BA Boeing $GD General Dynamics Consumer & B2B Robotics $XIACF Xiaomi $RR RichTech Robotics $SERV Serve Robotics Batteries $EOSE Eos Energy $QS QuantumScape $MVST Microvast $FLNC Fluence $KULR KULR $SLDP Solid Power $AMPX Amprius

Haven’t been using macbook for a month with this. - Run multiple coding agents in vps - Automation across multiple agents - Voice agents to manage all agents - Push notifications via PWA - All agents self aware of all other agents

China just released a desktop automation agent that runs 100% locally. It can run any desktop app, open files, browse websites, and automate tasks without needing an internet connection. 100% Open-Source.

We raised $8m to build self-healing software. In 2026, software moves fast. But monitoring and observability are still manual and slow. @sazabi is a next-generation observability platform for fast-moving engineering teams. Not another AI SRE. Not another LLM observability tool. A new, general solution to observability that works for any workload (including agents) and leverages AI for maximum speed and automation. Time to suit up.

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.