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Introducing ZERION Agent on Heurist Mesh! 🧩 This powerful portfolio tracking agent gives you instant insights into any EVM wallet's tokens and NFTs through simple natural language queries. Ask about holdings, track asset performance, and get detailed analytics - all powered by Zerion

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16,041 görüntüleme • 1 yıl önce •via X (Twitter)

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Introducing CashClaw — a brand new agent framework inspired by OpenClaw🦞, designed to do one thing and one thing only: make you money and get better at making you money. It's simple. You run the agent locally and set a specialization. The agent finds work. Delivers. Gets paid. Reads feedback. Learns from it. Finds better tools. Documents what to do and what not to do. Finds more work. Gets paid more. Autonomously. Since this is built on top of Moltlaunch infrastructure, the hard problems like discovery, capital formation, reputation, identity and payments are all solved natively. Open source. Dropping later this week.
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Remember when we as football fans had to rely solely on paper draft guides, sports radio rumors, and gut feelings to predict draft day decisions? Excited that fans now have access to the NFL's Draft IQ powered by Amazon Web Services ( – the most sophisticated tool yet for following the NFL draft and your favorite team's strategy. Draft IQ is built on Amazon QuickSight, our cloud business intelligence service that makes it easy to analyze and visualize massive amounts of data. QuickSight processes real-time data to give fans unprecedented insight into team decision-making, updating the entire draft landscape every five minutes. You can explore team needs, draft capital, and front office tendencies through personalized team dashboards, plus get AWS-powered machine learning predictions about potential trades and picks. During draft week, fans can track picks, prospects, and Next Gen Stats in real-time. We're also introducing Amazon Q Business integration, our generative AI-powered assistant. Q Business leverages large language models to understand and respond to natural language queries, allowing fans to ask detailed questions about draft prospects, team strategies, and historical draft data. It can provide AI-generated insights based on the same historical Next Gen Stats research data that powers Draft IQ, giving fans a new way to engage with the draft experience (check out the example below). Can't wait to see what stories the data tells us as teams make their selections and excited to dig into the Giants' data myself :)
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I stack Hermes agents with OpenClaw for financial research, and the results should be illegal. I track every politician, insider trader, and I know EXACTLY what moves they're making. If you can't beat them, join them. The exact playbook for printing money from insider trading (copy me): Requirements: • OpenClaw setup • Hermes Agent setup Step 1. Define your research thesis Before you send any prompts to either tool, you'll need to clarify exactly what you're trying to research. This could be: a specific industry, asset class, market sector, and so on. Examples: • Tracking smart money buys in the semiconductor industry • Tracking smart money buys in crypto • Tracking a specific politician and where they're bidding (like Nancy Pelosi) Step 2. Deploy Hermes agents to track the smart money (in parallel) Hermes is your data layer. Spin up 5 agents at the same time, each with one job: Agent 1: Track every politician's disclosed trades from the last 30 days (House and Senate stock disclosures) Agent 2: Pull insider transactions (Form 4 filings, CEO/CFO buys and sells) Agent 3: Scrape X sentiment from top 50 accounts on the topic Agent 4: Pull on-chain data (whale wallets, TVL, exchange flows) *if applicable* Agent 5: Monitor news, regulatory filings, and announcements from the last 30 days Each agent runs independently. You're not waiting for one to finish before the next starts. Step 3. Consolidate the output Once your Hermes agents finish, dump every output into a single document. (don't filter or summarize) - you want OpenClaw to see the raw data. Step 4. Feed it all into OpenClaw Open OpenClaw and paste the consolidated research file with this prompt: "Act as an elite macro analyst. Below is raw data gathered from multiple sources on [thesis], including politician disclosures and insider transactions. Synthesize the findings, identify the strongest signals and contradictions, flag any unusual smart-money activity, and give me a clear directional view with conviction levels. Flag any data gaps that need follow-up." OpenClaw will go deep, run its own reasoning chain, and produce a synthesized report. Done. Now you're literally tapping into the financial data they don't want you to see (it's all public - you just had to find it). Make sure to save this playbook so you don't lose it!

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Chat, meet Otto, an autonomous AI Agent powered by Hybrid Our new friend is launching its token $OTTO, which will give its holders access to multiple utilities, such as unique crypto insights and interactive features. By now you probably have guessed it - the Private Round of $OTTO launch is coming to Seedify on 5th-6th December (yes, tomorrow 😉) at super LOW FDV and fully unlocked! All T6-T9 $SFUND stakers will be automatically whitelisted for the sale. Basically, you just need to show up guys! Get to learn more about Otto and the upcoming Private Round in the article ⬇️

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Introducing the BIOS API: Turn Your Agent Into a Research Scientist Built to: 🦞 Add biomedical workflows to your OpenClaw🦞 agent 🧠 Create research or health agents w/ on-demand scientific intelligence 🧪 Pay per query via x402 on Base Any agent or app can now tap into the BIOS AI Scientist, plugging BIOS into the broader agent economy. What is BIOS? BIOS is an AI Scientist designed to handle complex biomedical research by orchestrating specialized scientific subagents. Ranked #1 on the leading bioinformatics benchmark, BIOS is already being used by 1,000+ researchers and labs to build new drugs and medicines. An Agentic Economy for Science AI agents have proven they can form multi-billion dollar ecosystems. BIOS applies the same primitives to drug discovery pipelines and health. Instead of coding bots and personal AI assistants, think research agent swarms running on a modern scientific stack. Imagine an OpenClaw agent built for longevity: It scans new literature daily, generates novel compound hypotheses through BIOS, designs validation workflows, and routes the best candidates to wet-lab funding - all programmatically. Connect it with an agent for microbiome health, enabling agent “backrooms” that autonomously surface cross-disciplinary insights. Micropayments for Scientific Work via x402 Each query triggers payment routing to BIOS and whichever subagents contribute to a response. The best agents earn. Usage settles instantly across contributing sources. The goal is pay-per-task science: paying for a CRISPR assay result, licensing a genomic dataset, or triggering a clinical data query - all settled in seconds via USDC. No purchase orders. No grant bureaucracy. No middlemen. x402 is the payment rail that makes agent-to-lab commerce possible - letting capital and cognition route themselves to the highest-signal science. What Will You Build? Drug discovery copilots? Longevity scouts? Automated literature monitors? Scientific due diligence agents? We’ll soon share the first implementations of the BIOS API. Stay tuned and see below for instructions on generating an API key for your agent or use-case.

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FilterSpy is now live! 🕵️ FilterSpy is a social AI agent on Telegram, disguised as a user. It can monitor messages in real time, join any public Telegram group, forward messages with custom filters, and generate AI-powered summaries. 🔹 Smart Message Forwarding – Just select users you want to track, and FilterSpy will forward their messages to you, with options to filter by keywords, just include or exclude what you need. 🔹 Personalised AI Summaries – Get custom summaries of selected users messages, simplified for tech jargon, topic-focused, or in any language you choose. 🔹 Access To Restricted Groups – FilterSpy can solve human verification tests to enter groups protected by channels and portals. Deep dive coming soon 👀 Access here - Documentation -

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Phase 2 is now complete ✅ Sei v2 mainnet beta is officially here and It’s the most performant EVM blockchain ever built. The future starts here, read more about the Sei vision and the journey ahead here: One thing is clear since the recent launch of the first parallelized EVM: deployments and on-chain activity are up and to the right. Looking ahead, the Foundation’s focus will truly be on builders; we invite developers and innovators to join us on this journey. If you are an EVM builder, you are a Sei v2 builder. To get started, check out the recently revamped Sei docs here: Explore some of the teams and projects that are live and building on Sei v2 👇 DeFi 🏦 🚜 Liquid staking with Silo 👂 Borrow and Lending with Yei Finance 🐉 Exchange ERC20 & CW20 tokens with DRAGONDEX ツ Create & trade memes on Sei with no coding experience with ツmeme.trade (🟩,🟩) 🗿 Orderbook like DEX with Bancor & Carbon DeFi 🪼 Provide liquidity and trade a diverse range of assets with jellyverse 🦄 Bridge, trade, and deploy positions on Uniswap v3 contracts through Oku Trade 🐼 🎰 Explore prediction markets, sports books and PvH games with @gamblino_app 🌬️ Gain early access to projects on Sei and launch tokens without the need of any developer experience with TAILWIND LABS 🟩 Cross-chain aggregator, enabling seamless swaps with on-chain providers with Rubic 🌟 Decentralized trading with AMM swaps, limit orders, and perpetual swaps with XEI 🍲 Options and fixed lending strategies with MYSO 🪸 Aggregate swaps for optimized rates with OpenOcean - An EVM + Solana DeFi Aggregator ✨ Participate in AI-powered prediction markets and trend analysis with PredX | Staked Media ⚡️ Launch, trade, and explore new tokens with @seiyandotfun NFTs 🎨 🌊 Leverage rapid finality and high throughput for NFTs with OpenSea 🟠 Buy, Sell, and trade your favorite NFTs on Sei with Pallet Exchange | The Sei Marketplace 🕺 Utilize tools and standards for easy NFT creation, management, and distribution, all via Lighthouse by WeBump Bridges 🌁 ⭐ Explore seamless interoperability and efficient cross-chain transactions with Stargate 🐙 Bridge from the wider EVM ecosystem with Symbiosis 0️⃣ Deploy applications on Sei v2 with LayerZero Labs 🦑 Swap tokens and access apps across EVM and Cosmos with squid in just one click 🌉 Bridge ETH from EVM chains to save on gas fees while exploring Sei's ecosystem with Merkly Wallets 👛 🔐 Stay secure with encrypted chats, track NFT drops, connect with DeFi communities, and share your insights— all with @SeiChats 💸 Manage assets with decentralized custody using Protofire | Token Utility Engineering, a multi-sig wallet utilizing Gnosis Safe 🐰 Ensure safe and seamless EVM interactions with the open-source Rabby Wallet Wallet 🧑‍💻 Unlock with Face ID/fingerprint and enjoy auto-token/NFT indexing with @Seif_Wallet 🧭 Connect to both EVM & Wasm based apps with Compass Wallet | Sunset on 28th May 🪄 Seamlessly onboard users and empower ecosystem developers with Magic Labs 🔓 Utilize a comprehensive MPC wallet platform and web3 gateway with FORDEFI Analytics & Data 🤓 🏦 Track and analyze your tokens, NFTs, and assets with DeBank 🔮 Access 500+ real-time feeds and on-chain randomness with Pyth Entropy on Sei v2 with Pyth Network 🔮 🏗️ Enjoy fast & reliable data for your Sei dapps. Build subgraphs with The Graph in Subgraph Studio 👣 Track the Sei blockchain with the comprehensive explorer from Seitrace 💧 Access NFT data, create and fill NFT orders, and build trading into your app with Reservoir 📊 Access on-chain data and learn through the Sei Academy with Flipside 📈🤖 💜 Get a high-level view of key metrics with the Sei ecosystem page by 👉 follow @Artemis 💪 Ensure proactive security and risk prevention with HypernativeLabs 🌟 Sei Creator Fund to support v2 growth with Gitcoin Charts for Sei V2 ​💹 🎯 Defined 🦅 DEX Screener 🦎 GeckoTerminal ⛓️ Chainspect This is just the beginning for Sei v2. With new teams joining daily, we're parallelizing the future. Stay tuned as we push the boundaries of innovation and fulfill the Sei vision of scaling the EVM 🔴💨

Sei

186,627 görüntüleme • 2 yıl önce

We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨
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We’d like to share some updates from within the Forge. While minor updates may roll out at a slightly slower pace, our primary focus is dedicated to an exciting upcoming feature: Machina Foundry. What is Machina Foundry? Machina Foundry is an AI Agent Builder Platform that allows users to define an agent's purpose, functions, and objectives through simple, natural language prompts. Once an agent is created, Alchemists can seed liquidity in $ALCH for their agent. Liquidity is placed in Meteora pools, with 50% allocated to the ALCH ecosystem and the remaining 50% locked permanently. This structure ensures the ecosystem benefits from pool fees, enabling periodic ALCH token buybacks and supporting long-term growth. Additionally, the Foundry introduces a flywheel effect: purchasing an agent requires acquiring ALCH tokens, further integrating the ecosystem with the token economy. Agents built in Machina Foundry are fully customizable and reflect unique personalities. They can create apps and tools tailored to their character, powered by Alchemist AI’s robust technology. While similar to Azarus, these agents bring an added layer of individuality, ensuring that their creations vary significantly based on their distinct traits and configurations. Imagine a network of thousands of AI agents, each contributing diverse applications and tools, driving creativity and value across the ecosystem. Now that’s Magic!🪄✨

ALCHEMIST AI 🔮

72,130 görüntüleme • 1 yıl önce

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.
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LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

Avi Chawla

30,762 görüntüleme • 8 ay önce

The AI Agent Terminal (Public Beta) is LIVE. Trade, analyze, and strategize, all in natural language. 🚀 With Terminal Public Beta: ✨ Revamped platform + Lander page 📖 New docs + Educational content pages from Gen3 ⚡ Streamlined UX + UI What can the AI Agent Terminal do? - AI-Powered Swaps → Trade instantly with plain text. - AI Market Analysis → Hourly updates + daily recaps. - Automated Tasks → Price alerts, rebalancing, recurring actions. - Strategy Building → Create + run strategies in natural language. - Advanced Transactions → Complex XRPL ops made effortless. - External Wallet Integrations → Works with Joey Wallet, Xaman® Wallet 🪝 + more. Pricing: - Terminal = Free - Inference = Very cheap, we are always looking for the best model rates - Link your Aigent Pass NFT holdings for discounted inference costs - Pay for inference balances directly with $AIXRP 🌍 Why it matters: AI + DeFi aren’t hype anymore, they’re live, accessible, and ready for you on XRPL. This is just the beginning. More agentic power is coming! Are you ready to enter the Terminal? Please bring all feedback to our Discord or Telegram.. we’re building this together. 💬
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The AI Agent Terminal (Public Beta) is LIVE. Trade, analyze, and strategize, all in natural language. 🚀 With Terminal Public Beta: ✨ Revamped platform + Lander page 📖 New docs + Educational content pages from Gen3 ⚡ Streamlined UX + UI What can the AI Agent Terminal do? - AI-Powered Swaps → Trade instantly with plain text. - AI Market Analysis → Hourly updates + daily recaps. - Automated Tasks → Price alerts, rebalancing, recurring actions. - Strategy Building → Create + run strategies in natural language. - Advanced Transactions → Complex XRPL ops made effortless. - External Wallet Integrations → Works with Joey Wallet, Xaman® Wallet 🪝 + more. Pricing: - Terminal = Free - Inference = Very cheap, we are always looking for the best model rates - Link your Aigent Pass NFT holdings for discounted inference costs - Pay for inference balances directly with $AIXRP 🌍 Why it matters: AI + DeFi aren’t hype anymore, they’re live, accessible, and ready for you on XRPL. This is just the beginning. More agentic power is coming! Are you ready to enter the Terminal? Please bring all feedback to our Discord or Telegram.. we’re building this together. 💬

aigent.run

25,889 görüntüleme • 11 ay önce

more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.
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more frontend vibecoding tips (results below): WHY YOUR VIBECODED FRONTENDS ALL LOOK THE SAME AND SUCK: when asked to make a frontend, the agent/llm will default to the center/average of its training data (in a very loose sense). through the training process, the model essentially converges on some default UI style. it's very capable of doing things that are different from this style, but you have to ask! for instance, ChatGPT tends to reply in the same tone for all users untill you interact with it and instruct it differently ("be sassy", "eli5"). the second reason is that most of us are not good at coming up with designs and describing them precisely (see my tweet on a crash course in common components, which i'll link below). treat frontend generation just like any other eng task! you need to provide a good detailed spec. TIPS: 1. give ur agent screenshots of designs you like (you may not know the right words to describe them but the agent will! a pic = 1000 words) where to find ui inspo? Behance, Dribbble, Mobbin (Mobbin is paid but worth it!) 2. ask ur agent for proposals, this helps "seed" different directions so the final frontend stands out. don't be afraid to go back and forth. 3. ban certain tendencies: no Inter/Roboto, no shadcn (controversial), no gradients, no emojis 4. encourage the agent to be extreme and make bold decisions, not safe ones. i think that the underlying models tend to get taught during RL/fine-tuning to make conservative choices that produce reasonable but boring frontends 5. give ur agent Figma MCP. the best results will come if you mockup your vision in Figma first. 6. Ideally choose an agent with vision capabilities TLDR: Most people are tremendously underusing agents for frontend design. They are much better than you might expect.

andrew gao

64,546 görüntüleme • 5 ay önce