The Growth Engine for the Agent Economy

Onchain
Joined March 2025
Most agents are built to take a goal and finish it alone. Manus plans and executes end-to-end on its own cloud computer, then hands back a result. Grok Bot is a persistent teammate on a shared cloud computer: real apps, multi-step work, 24/7 coordination. Both are strong at autonomous task completion. Teamily is different. It is a human–agent social platform where people and custom agent teams work in the same chats, groups, and studios, with unified living memory and multi-model routing. Agents are first-class members, co-creating sites, docs, slides, and more—not a job you fire off. Others complete tasks. Teamily is the shared space where humans and agents keep working together.
150,000 small business owners and employees are already using Teamily AI. Today, we're opening it to everyone: your personal AI agent and an entire team of AI agents, ready to work for you and your business. Meet Teamily AI 2.0 — the human–agent platform where you and always-on AI agents get work done together in one unified, context-aware space. We've taken four major capabilities to the next level to help businesses build and grow faster: 1. Real-Time Human–Agent Collaboration. Humans and AI agents work together across chats, meetings, studios, and communities to research, analyze, and create websites, dashboards, videos, slides, documents, and more. 2. Unified Context & Living Memory. One connected context across conversations, meetings, channels, and workspaces. Your AI agents remember, learn, and understand you over time—delivering smarter, more personalized results. 3. Custom Agents & Agent Teams. Create and orchestrate AI agent teams in one click. Manage agents through Agent Workspace, connect them to Telegram, WhatsApp, iMessage, and Slack, or integrate them into your products via Agent API. 4. Intelligent Multi-Model Routing. Our proprietary models work alongside leading models from OpenAI, Anthropic, Gemini, DeepSeek, Qwen, Kimi, MiniMax, and more—automatically routing each task to the best model across text, image, video, and voice. Teamily AI 2.0 is built for every business owner, every employee, and every customer. America has 36 million small businesses. 98% have fewer than 20 employees. Many are teams of one. At Teamily, we believe AI should democratize opportunity, giving everyone the power to achieve more. You have the business. Now you have the team. Try Teamily AI 2.0 for free → teamily.ai
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order your oki home -> Personal AI Computer okihome.ai
Say hello to Oki Home, your Personal AI Computer. We're building a future of limitless, personalized intelligence for every consumer, while keeping all your data in your hands. Reserve our first batch, shipping mid-december! okihome.ai
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Pearl 不是算力市场:你的显卡不用「接」到任何地方 常有人以为,参与 Pearl 要把 GPU「接到」某个网络上去领任务。Omri 5/12 回应质疑时专门纠正过 👇 🦪 你照常在本地用 vLLM 跑模型,区别只是 Pearl 版 vLLM 把普通的矩阵乘法 kernel(TRT、cuBLAS、CUTLASS 等)换成了 Pearl 的 GEMM kernel 🦪 任务不用发到外面,Omri 的原话是「没有带宽开销、没有延迟」。kernel 本身的计算开销是另一回事,他 9/25 说当前 INT8 版约 10–15% 🦪 推理中的矩阵乘法挖到区块时,网关只提交一份很便宜的 zk 证明,不泄露权重和激活值的任何信息。Omri 说,否则闭源模型公司永远不会用 Pearl 🦪 L1 工作在矩阵乘法(GEMM)这一层,与模型无关,新增模型不需要分叉:Gemma 4 就是主网上线后才支持的,没做任何升级 🦪 要分叉的是底层能力升级,比如支持 MoE 层、融合 kernel、FP8/FP4 原生数据类型 补两句背景。「与模型无关」说的是链的规则:眼下主网是 INT8 版,模型得先量化成 Pearl 格式,Omri 9/25 也承认大多数原生浮点模型用不上。另外主网也不只为加功能分叉过:6/12 上了 MoE 硬分叉,后来从 91630 高度起又改成不收 MoE 证明。 理解 Pearl,先把它当成嵌在推理里的一层「挖矿 kernel」,而不是撮合算力买卖的平台。 参考: Omri 谈模型无关 xitter.cf/WeinsteinOmri/status/2… Omri 9/25 谈 INT8 开销 xitter.cf/WeinsteinOmri/status/2… MoE 硬分叉 xitter.cf/prlnet/status/20653261… GitHub pearl-research-labs/pearl(node/chaincfg/params.go) xitter.cf/WeinsteinOmri/status/2…
hmm.. i think you completely misunderstood the technology and this discussion will be more productive if you read our whitepaper.. Pearl is *not* a marketplace -- you don't "point" your GPU at pearl -- you run your model locally as usual on vLLM, except our vLLM calls Pearl's GEMM kernels instead of vanilla GEMM (TRT/CUBLASS/CUTLASS etc). No bandwidth overhead, no latency, no nothing. I recommend you simply try it on our Github and see for yourself :) Re your first question, that's the point of zk-proofs (our block-opening condition it actually on intermediate-tiles, but it wouldn't matter, output works as well) -- once your LLM finds a winning block (during inference matmuls), our gateway communiates a (very cheap) zk-proof that reveals exactly 0 information about weights/activations (otherwise, you're absolutely right that closed-source model companies would never use Pearl). Re hw types -- we will eventually expand Pearl-GEMM kernerls to all popular hardwares (even beyond GPUs..), we're already on it, but pls be patient..
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SpreadX AI retweeted
Introducing ScienceBuddy — a free workspace for scientific agents that improve through researcher collaboration. Use GPT-6 in ScienceBuddy at no cost. GPU-accelerated, and fused with the JEV framework. 🧵 Two loops: 🔹 Inner loop — refines the agent harness 🔹 Outer loop — trains the model with rubric-guided RL Together: Recursive-in-Recursive Self-Improvement. ScienceBuddy explores how scientific agents can improve through sustained collaboration with researchers. 🔬Try it free: science-buddy.io #ScienceBuddy #PhAILabs #AI4Science
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reply now!
Time to trade Alpha 1.0 gave testers access to our core set of RWA and crypto perps. The result? Multiple new builds that have improved your trading experience; better charts, UI refinements and app speed optimization. But it’s time to forge ahead with new opportunities for even more traders. We’ve now removed key constraints so that you can trade larger size with better execution: 📷 Deeper liquidity across all of our core perpetual futures markets 📷 Futures deposit limit increased to $5,000 USD 📷 API trading permitted This new phase remains closed alpha. We are gradually expanding access, making sure each wave of users is getting a first-class experience before we invite another wave. If you’re interested in trading with us, please reply below within 24 hours.
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Good day to be a builder on this. We spent the last three weeks building Incarna on AWS @awscloud AgentCore Payments with BlockRun @BlockRunAI. Today most agents borrow their user's identity. Your email, your social accounts, your credentials, your card. Incarna gives an agent its own: an inbox, a wallet, a device environment, a cryptographic identity, and a history that accumulates into reputation. Something it can persistently exist and operate through. Your agent has a mind and a wallet. Incarna gives it a body. Opening to beta users next week.
Agents are getting really good at reasoning and taking action. Paying for something has been a lot harder. AgentCore Payments is now GA with @coinbase and @stripe, giving agents a managed way to pay for APIs, content, data feeds, and even other agents, with spending limits and observability built in.
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Jarvix is 🔥
🚀 Global Launch: Jarvix, Your Context OS is now live! Meet the next generation of personalized AI built around your context, your taste, and your way of thinking. #JarvixOS transforms how you work with AI by understanding your patterns, carrying your context across agents, and helping you move from ideas to action. Step into a new era of AI collaboration: • Discover your AI-native archetype • Build your personal AI model from your evolving AI interactions • Never start from zero - your context moves with you across sessions • Coordinate Codex, Claude Code, Gemini, Hermes, OpenClaw, and more as one connected AI team. • Turn insights into your next move, with you always in control Instead of adapting yourself to every agent, @Jarvixdotlive carries the context you choose, helps you understand what it reveals, and brings the right agents together when you decide to act. Your AI tools shouldn’t work like separate assistants. They should work like one team. That’s the future of AI: Not more agents. One shared context. One Jarvix.
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Launching new tokens today still means navigating tradeoffs across flexibility, speed, and security. @flapdotsh is building a secure launch stack for EVM chains: • Custom programmable token launches • A no-code CA template store • Verifiable on-chain AI reasoning via Flap AI Oracle In a few months, they've gone from hackathon project to a profitable team of 8 backed by a $60K angel round. Catch Flap at EASY Residency S3 demo day.
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Honored to receive ASGCT Outstanding New Investigator Award with amazing group of fellow recipients. Back in Boston — where my CRISPR-Cas9 journey began — felt like coming home. 🧬 Big thank you to my mentor and collaboratos @zhangf @geochurch @Joseph_C_Wu @aviv_regev @Matthew_Porteus and our incredible lab members and partners! @Stanford @StanfordMed @NVIDIAHealth @AI4S_Catalyst My talk "From Code to Cure": closing the loop between AI that reasons (CRISPR-GPT) and AI that experiments (LabOS, LabClaw) — so hypothesis → experiment → therapy becomes one continuous, self-improving system. The road is long. The path forward has never looked more exciting! 💊 #ASGCT2026 #CRISPR #AI4Science #AIforScience #biotech #GeneTherapy #FunctionalGenomics
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SpreadX AI retweeted
Doomscrolling was passive. Now you can trade the future. Introducing Beep Predict Trader R3: prediction markets in a feed. Two modes: Manual Predict (swipe) + AI Predict (autopilot 24/7). 🧵
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SpreadX AI retweeted
In 2016, a PhD student at Google Brain used a "lazy" math shortcut to solve a coding problem. That shortcut helped birth the Transformer architecture. He then took those insights to Wall Street to manage a $1B portfolio. The @BillSun_AI interview. Here are 7 insights on the future for innovators: 🧵
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SpreadX AI retweeted
Thrilled to announce @BlockRunAI has been accepted into Base Batch 3! 🎉 This wouldn't have happened without the incredible x402 and CDP teams — @programmer @x402intern @DukeOphir @Must_be_Ash @fabdarice, you built something we genuinely love working with. A heartfelt thank you to @luca_curran for showing up when it mattered most — knowing you're in our corner means everything. To @BronheimDaniel, @davidtsocy, and @jonathankingvc — thank you for your belief and trust in us from the very beginning. And to @kleffew94 and @x402intern — your encouragement on day 1 carried us further than you know. Proud to be building in the @base ecosystem. 🔵
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SpreadX AI retweeted
AI becoming the main on-chain user. Blockchains provide what agents need to operate at scale: fast, cheap, permissionless access to capital. As agents grow, economic activity shifts with them, contributing to Machine GDP (mGDP). Beep is building the finance stack that enables this transition.
.@RaoulPal: AI agents can't move forward without crypto. @0xbeepit CEO: Pure AI builders don't care about token price - they care about fast, cheap, permissionless rails. "It's becoming more and more clear that AI is an onchain user."
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SpreadX AI retweeted
I asked @ZakFolkman a tough question in Hong Kong: What makes USD1 capable of competing with USDT/USDC? His answer: USD1 isn’t trying to be just another stablecoin — it aims to upgrade money itself. New Y TALK Episode Live Watch Guide: → Stablecoins will become the base layer of the AI economy → Wall Street is already in → USD1 vs USDT vs USDC — the real difference → Why money needs an upgrade, and why now -------------------🦅☝️------------------- 在香港问了 @zakfolkman 一个很尖锐的问题: USD1 凭什么跟 USDT/USDC 抗衡? 而他说: USD1想做的不是又一个稳定币,目标是完成货币的升级 Y TALK 最新一期 观看指南: → 稳定币将成为 AI 经济底层 → 华尔街已经入场 → USD1 vs USDT vs USDC 真正的差距 → 货币升级,为什么是现在 没想到我的英文也能全英采访了,欢迎来看!(有配双语字幕😝)
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