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I’ve been testing a new AI agent that actually takes enterprise security seriously. Meet PokeeClaw by Pokee AI. → Enterprise-secure → Zero setup → 70% fewer tokens → 1,000+ app integrations 🔥 3 wild use cases 🧵↓ 1/ Google Drive connection and deep analysis

Charly Wargnier

171,260 subscribers

39,196 次观看 • 4 个月前 •via X (Twitter)

教育健康养生科学技术

Anya Rossi• Live Now

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OpenClaw doesn't belong in production. We built PokeeClaw — enterprise-secure AI agents, zero setup, 1,000+ app integrations. Try now: First 500 to follow Pokee AI, comment “PokeeClaw”, like & repost get 1 month free.

OpenClaw doesn't belong in production. We built PokeeClaw — enterprise-secure AI agents, zero setup, 1,000+ app integrations. Try now: First 500 to follow Pokee AI, comment “PokeeClaw”, like & repost get 1 month free.

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Google AI

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Factory

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I got tired of explaining myself to AI every single day. Same context. Same workflow. Same instructions. Copy-pasted into every new session like it’s 2022. So I tried Panofy. Uploaded my own scripts and documents to train an agent — then gave it a single instruction. 🔥 It ran the task. Got it right. First time. No prompt loops. No setup. It just… knew. The thing that surprised me most? It actually improves the more you use it. Learns from mistakes. Builds memory. Adapts to how you think. Fewer tokens, better results. I’ve used a lot of AI tools. This one made me feel like I finally own mine. Panofy isn’t just another tool — it’s the best AI agent for expert-level tasks. If you’re serious about building with AI, this is worth trying. Sign up and get 10,000 free credits + 7-day Panofy Plus free trial 👉 #AI #AIAgents #Productivity

I got tired of explaining myself to AI every single day. Same context. Same workflow. Same instructions. Copy-pasted into every new session like it’s 2022. So I tried Panofy. Uploaded my own scripts and documents to train an agent — then gave it a single instruction. 🔥 It ran the task. Got it right. First time. No prompt loops. No setup. It just… knew. The thing that surprised me most? It actually improves the more you use it. Learns from mistakes. Builds memory. Adapts to how you think. Fewer tokens, better results. I’ve used a lot of AI tools. This one made me feel like I finally own mine. Panofy isn’t just another tool — it’s the best AI agent for expert-level tasks. If you’re serious about building with AI, this is worth trying. Sign up and get 10,000 free credits + 7-day Panofy Plus free trial 👉 #AI #AIAgents #Productivity

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33,551 次观看 • 3 个月前

Introducing the new Box Agent. The Box Agent works across your entire Box file system, maintaining all your security and access controls, and is hyper tuned for working with enterprise content. This means you can now ask questions from all your enterprise content, search for files that were impossible to find before, deploy an agent on specific tasks on subsets of documents, analyze complex data sets, and generate or edit documents and spreadsheets via the agent. You can have the Box Agent search across your Box account to prepare for a sales meeting, analyze customer sentiment reports, process a large set of contracts for legal risk, provide insights into product development, leverage existing knowledge to answer RFPs, and thousands of other use-cases. 90% of enterprise data is unstructured data. This means most enterprise knowledge is sitting in inside of research reports, marketing assets, presentations, roadmap files, contracts, HR documents, and more. This is the critical context that agents need to be able to answer questions about a business, automate workflows, or serve up to other agents. We’ve been grinding on this for a quite a bit, and due to recent AI model advancements we’re now ready to release it to customers. Previous model generations had a difficult time knowing when to give up or keep going on a search, when to browse for files vs. use queries, how to rank files appropriately to know which version of content to use, how to handle large amounts of context to comb through, and more. Due to recent breakthroughs from models like GPT-5.4, Opus 4.6, and Gemini 3, we’ve seen major gains in tool calling, code execution, advanced reasoning, and more. Combined with an agent harness tuned to Box context, now it’s finally possible to have an agent that can work across your file system on long running tasks and actually deliver high quality results. Best of all, because the Box Agent works with any leading AI model, you’ll quickly get the gains coming out of the major labs as major new models are released. Further, openness at Box is key, so you’ll be able to call up the Box Agent from Box’s APIs and MCP server, so you can interact with Box intelligently from any other AI system. We know work happens everywhere, and we want to ensure you can access to the content you need from those places. The new Box Agent is available starting today, rolling out now for Enterprise Plus and Enterprise Advanced customers.

Introducing the new Box Agent. The Box Agent works across your entire Box file system, maintaining all your security and access controls, and is hyper tuned for working with enterprise content. This means you can now ask questions from all your enterprise content, search for files that were impossible to find before, deploy an agent on specific tasks on subsets of documents, analyze complex data sets, and generate or edit documents and spreadsheets via the agent. You can have the Box Agent search across your Box account to prepare for a sales meeting, analyze customer sentiment reports, process a large set of contracts for legal risk, provide insights into product development, leverage existing knowledge to answer RFPs, and thousands of other use-cases. 90% of enterprise data is unstructured data. This means most enterprise knowledge is sitting in inside of research reports, marketing assets, presentations, roadmap files, contracts, HR documents, and more. This is the critical context that agents need to be able to answer questions about a business, automate workflows, or serve up to other agents. We’ve been grinding on this for a quite a bit, and due to recent AI model advancements we’re now ready to release it to customers. Previous model generations had a difficult time knowing when to give up or keep going on a search, when to browse for files vs. use queries, how to rank files appropriately to know which version of content to use, how to handle large amounts of context to comb through, and more. Due to recent breakthroughs from models like GPT-5.4, Opus 4.6, and Gemini 3, we’ve seen major gains in tool calling, code execution, advanced reasoning, and more. Combined with an agent harness tuned to Box context, now it’s finally possible to have an agent that can work across your file system on long running tasks and actually deliver high quality results. Best of all, because the Box Agent works with any leading AI model, you’ll quickly get the gains coming out of the major labs as major new models are released. Further, openness at Box is key, so you’ll be able to call up the Box Agent from Box’s APIs and MCP server, so you can interact with Box intelligently from any other AI system. We know work happens everywhere, and we want to ensure you can access to the content you need from those places. The new Box Agent is available starting today, rolling out now for Enterprise Plus and Enterprise Advanced customers.

Aaron Levie

44,515 次观看 • 4 个月前

In our latest Box AI Enterprise Eval, we tested Paul Jankura’s Claude 4 Sonnet and Opus models, now integrated into Box AI, across enterprise Q&A tasks, technical workflows, and advanced coding scenarios—revealing major advancements in developer productivity and content intelligence. AI-assisted coding and development just reached a new milestone! Here's what we discovered: Claude 4 significantly improves understanding, generating, and debugging code across multiple programming languages. Developers can: ↳ Accelerate code generation ↳ Improve debugging ↳ Enhance technical documentation ↳ Build smarter AI agents 👉 Automating Financial Analysis with Code Generation: We evaluated Claude 4 by using the Box AI API to analyze ten complex 10-K financial reports. Claude 4 dynamically generated Python code to fetch file IDs from a Box folder, automating data extraction. Within two minutes, it accurately extracted key company data such as revenues, metrics, and highlights—demonstrating its potential to streamline demanding analytical tasks. 👉 Understanding Enterprise Content: Our evaluation confirms Claude 4 maintains strong performance on enterprise Q&A tasks, effectively extracting precise details from single documents and reliably synthesizing information across multiple sources. This ensures seamless integration of structured and unstructured data alongside powerful coding capabilities. 🔓 Developer-Centric Use Cases Unlocked: Organizations can leverage Claude 4 within Box AI to: ↳ Create custom engineering agents referencing technical documents stored in Box, pulling real-time data from Jira, or finding solutions on Stack Overflow. ↳ Build intelligent technical support bots capable of analyzing user-provided code snippets against internal manuals. ↳ Automate secure code reviews by evaluating repository code (stored in Box) against security policies. ↳ Efficiently migrate legacy systems by translating old codebases into modern languages or platforms. Ready to empower your developers and accelerate innovation? To explore Claude 4 Sonnet and Opus through Box AI Studio and APIs, contact us at ailabs@box.com and request early access today! Learn more:

In our latest Box AI Enterprise Eval, we tested Paul Jankura’s Claude 4 Sonnet and Opus models, now integrated into Box AI, across enterprise Q&A tasks, technical workflows, and advanced coding scenarios—revealing major advancements in developer productivity and content intelligence. AI-assisted coding and development just reached a new milestone! Here's what we discovered: Claude 4 significantly improves understanding, generating, and debugging code across multiple programming languages. Developers can: ↳ Accelerate code generation ↳ Improve debugging ↳ Enhance technical documentation ↳ Build smarter AI agents 👉 Automating Financial Analysis with Code Generation: We evaluated Claude 4 by using the Box AI API to analyze ten complex 10-K financial reports. Claude 4 dynamically generated Python code to fetch file IDs from a Box folder, automating data extraction. Within two minutes, it accurately extracted key company data such as revenues, metrics, and highlights—demonstrating its potential to streamline demanding analytical tasks. 👉 Understanding Enterprise Content: Our evaluation confirms Claude 4 maintains strong performance on enterprise Q&A tasks, effectively extracting precise details from single documents and reliably synthesizing information across multiple sources. This ensures seamless integration of structured and unstructured data alongside powerful coding capabilities. 🔓 Developer-Centric Use Cases Unlocked: Organizations can leverage Claude 4 within Box AI to: ↳ Create custom engineering agents referencing technical documents stored in Box, pulling real-time data from Jira, or finding solutions on Stack Overflow. ↳ Build intelligent technical support bots capable of analyzing user-provided code snippets against internal manuals. ↳ Automate secure code reviews by evaluating repository code (stored in Box) against security policies. ↳ Efficiently migrate legacy systems by translating old codebases into modern languages or platforms. Ready to empower your developers and accelerate innovation? To explore Claude 4 Sonnet and Opus through Box AI Studio and APIs, contact us at [email protected] and request early access today! Learn more:

Box

285,687 次观看 • 1 年前

ElizaOS Ecosystem Map -- Version #3 🤖 AI Agent Framework (Core) 1) ElizaOS -- elizaOS 🧠 - Open source AI Agent framework - Cross-chain compatible (Solana, Base, EVM) - Supports plugins for social media, blockchains, and APIs 🏗️ Infrastructure 2) ElizaCloud ☁️ - Cloud hosting platform for AI agents - One-click agent deployments with scalability - Secure environments using TEEs 3) Jeju ⛓️ - Purpose-built L2 App Chain for Agents - High-performance blocks for sub-second agent coordination - The backbone of the decentralized Agent Network 4) Otaku -- @otakuonbase 👛 - DeFi wallet designed for AI agents - Supports agent-controlled crypto transactions (swap, send, hold) - Secure, non-custodial infrastructure for on-chain actions 🎮 Apps/Games 5) Spartan -- Spartan 🛡️ - ElizaOS's flagship agent showing what’s possible - Autonomous trading based on crypto knowledge - Trained on influencer data for market insights 6) Babylon -- Babylon -- The City of Agents 🐵 - Social prediction market game for agents - Agents compete alongside humans to forecast on-chain events - Includes perps and other gamified mechanics 7) Hyperscape -- Gold ⚔️ - First AI MMO Game powered by ElizaOS - A vast gaming world built for humans and agents to coexist - Agents drive the in-game economy and narrative 8) Milady App -- Milady on BSC 😎 - Open-source, local-first AI companion app powered by ElizaOS - Let's anyone quickly create and deploy their own agents - Built-in wallet, natively integrated with BNB chain 9) OTC Trading Desk 📊 - Multi-chain AI-powered OTC desk for crypto trades - Lists tokens off-market with transparent lockup and discount terms - Use Eliza agents to negotiate terms on your behalf

ElizaOS Ecosystem Map -- Version #3 🤖 AI Agent Framework (Core) 1) ElizaOS -- elizaOS 🧠 - Open source AI Agent framework - Cross-chain compatible (Solana, Base, EVM) - Supports plugins for social media, blockchains, and APIs 🏗️ Infrastructure 2) ElizaCloud ☁️ - Cloud hosting platform for AI agents - One-click agent deployments with scalability - Secure environments using TEEs 3) Jeju ⛓️ - Purpose-built L2 App Chain for Agents - High-performance blocks for sub-second agent coordination - The backbone of the decentralized Agent Network 4) Otaku -- @otakuonbase 👛 - DeFi wallet designed for AI agents - Supports agent-controlled crypto transactions (swap, send, hold) - Secure, non-custodial infrastructure for on-chain actions 🎮 Apps/Games 5) Spartan -- Spartan 🛡️ - ElizaOS's flagship agent showing what’s possible - Autonomous trading based on crypto knowledge - Trained on influencer data for market insights 6) Babylon -- Babylon -- The City of Agents 🐵 - Social prediction market game for agents - Agents compete alongside humans to forecast on-chain events - Includes perps and other gamified mechanics 7) Hyperscape -- Gold ⚔️ - First AI MMO Game powered by ElizaOS - A vast gaming world built for humans and agents to coexist - Agents drive the in-game economy and narrative 8) Milady App -- Milady on BSC 😎 - Open-source, local-first AI companion app powered by ElizaOS - Let's anyone quickly create and deploy their own agents - Built-in wallet, natively integrated with BNB chain 9) OTC Trading Desk 📊 - Multi-chain AI-powered OTC desk for crypto trades - Lists tokens off-market with transparent lockup and discount terms - Use Eliza agents to negotiate terms on your behalf

Seppmos

25,942 次观看 • 5 个月前

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 次观看 • 11 个月前

Our most intelligent workhorse model yet for coding and agents has arrived ⚡ Meet Gemini 3.7 Flash. — Crush that seemingly endless to-do list. Gemini Spark in the Google Gemini now uses 3.7 Flash. The new model can equip your personal AI agent to work even smarter for you by seamlessly handling complex, multi-step tasks across your Google Workspace apps like Gmail, Google Calendar and Google Docs — Enjoy a smoother build experience. The model thinks more diligently, putting more effort into multi-step planning and tool calls. A more disciplined execution means less manual oversight and fewer retries across engineering workflows — Build more, spend less. 3.7 Flash is available through the end of the year with an introductory price of half the original 3.6 Flash cost per million tokens ($0.75/1M input tokens and $3.75/1M output tokens)

Our most intelligent workhorse model yet for coding and agents has arrived ⚡ Meet Gemini 3.7 Flash. — Crush that seemingly endless to-do list. Gemini Spark in the Google Gemini now uses 3.7 Flash. The new model can equip your personal AI agent to work even smarter for you by seamlessly handling complex, multi-step tasks across your Google Workspace apps like Gmail, Google Calendar and Google Docs — Enjoy a smoother build experience. The model thinks more diligently, putting more effort into multi-step planning and tool calls. A more disciplined execution means less manual oversight and fewer retries across engineering workflows — Build more, spend less. 3.7 Flash is available through the end of the year with an introductory price of half the original 3.6 Flash cost per million tokens ($0.75/1M input tokens and $3.75/1M output tokens)

Google AI

123,607 次观看 • 9 天前

I made $16,900 in 72 hours trading Gold. Built a 3‑agent AI system with OpenClaw: - Agent predicts gold price - Agent executes trades on the Poly market - Agent takes profit I’ve written a step‑by‑step setup guide for this Gold AI trading bot — free for 24 hours. To get it: - Comment “Gold” - Like + Retweet - Follow Theo (so I can DM you) Gold is repeating 1979: war → oil 2x → crisis → dump. My AI ran 10,000 Monte Carlo simulations and found a 73.4% probability that gold hits $3,000. Poly market priced it at 18%. That’s not trading — that’s arbitrage. Result: $1,300 → $16,900 in 72 hours. 7 trades. 6 wins. 1 skip. Stop betting on vibes. Start trading with math. Don't forget to bookmark and follow me Theo

I made $16,900 in 72 hours trading Gold. Built a 3‑agent AI system with OpenClaw: - Agent predicts gold price - Agent executes trades on the Poly market - Agent takes profit I’ve written a step‑by‑step setup guide for this Gold AI trading bot — free for 24 hours. To get it: - Comment “Gold” - Like + Retweet - Follow Theo (so I can DM you) Gold is repeating 1979: war → oil 2x → crisis → dump. My AI ran 10,000 Monte Carlo simulations and found a 73.4% probability that gold hits $3,000. Poly market priced it at 18%. That’s not trading — that’s arbitrage. Result: $1,300 → $16,900 in 72 hours. 7 trades. 6 wins. 1 skip. Stop betting on vibes. Start trading with math. Don't forget to bookmark and follow me Theo

Theo

20,298 次观看 • 3 个月前

GT Protocol AI Digest No.93: Microsoft Wants AI Everywhere Here are five stories worth your attention 👇 📞 Google Wants to Catch Fake Callers Google's Phone app can now detect when a scammer is pretending to be someone from your contacts. The feature analyzes calls in real time and warns users about potential impersonation attempts. 🤖 Microsoft Builds an OS for AI Devices Microsoft unveiled Project Solara, a new operating system designed specifically for AI-powered gadgets. Instead of apps, the platform is built around AI agents that can perform tasks across devices. 🔓 Meta AI Helped Hack Instagram Accounts Researchers found that Meta's own AI systems could be manipulated into granting access to high-profile Instagram accounts. The incident exposed serious security weaknesses in AI-powered support tools. 📉 The AI Productivity Promise Is Under Pressure A new analysis argues that despite rapid improvements in AI capabilities, the massive productivity gains promised by the industry remain difficult to measure in the real world. 🛒 Amazon Invents Products That Don't Exist Amazon is testing AI-generated product images inside search results. Users may now see items that look real but aren't actually available for purchase.

GT Protocol

30,993 次观看 • 2 个月前

AGENCIES ARE CHARGING $50,000 FOR HEAVY, CLUNKY AUTOMATION, WHILE SOLO OPERATORS ARE SELLING THE SAME OUTCOME FOR $5k AND BUILDING IT IN JUST 3 HOURS Most people think building an AI agency requires an expensive stack of tools like n8n, Make, and Zapier to justify high monthly retainers They spend weeks pitching and designing overly complex “spaghetti” workflows for clients In reality, the better approach is to build an AI Operating System directly in VS Code using local Markdown files The cost gap is insane. You pay $20/month for a Claude account and spend a few hours wiring up ClickUp and Google Workspace APIs Then you package that same architecture as a $5k one-time setup and a $2k monthly retainer Right now, founders are paying $15k + for enterprise AI setups that a single operator can build with almost zero overhead And if you want a practical AI OS playbook, I’ve attached an article below Save this post and the article so you can come back later and learn how to build a full AI operating system in just 3 hours

AGENCIES ARE CHARGING $50,000 FOR HEAVY, CLUNKY AUTOMATION, WHILE SOLO OPERATORS ARE SELLING THE SAME OUTCOME FOR $5k AND BUILDING IT IN JUST 3 HOURS Most people think building an AI agency requires an expensive stack of tools like n8n, Make, and Zapier to justify high monthly retainers They spend weeks pitching and designing overly complex “spaghetti” workflows for clients In reality, the better approach is to build an AI Operating System directly in VS Code using local Markdown files The cost gap is insane. You pay $20/month for a Claude account and spend a few hours wiring up ClickUp and Google Workspace APIs Then you package that same architecture as a $5k one-time setup and a $2k monthly retainer Right now, founders are paying $15k + for enterprise AI setups that a single operator can build with almost zero overhead And if you want a practical AI OS playbook, I’ve attached an article below Save this post and the article so you can come back later and learn how to build a full AI operating system in just 3 hours

Bonsai 🌳

10,885 次观看 • 2 个月前

We've all experienced how consumer AI can help in our personal lives, but that same experience hasn't been available at work. Most enterprise data is siloed, consumer AI can't access your work tools, and many orgs won't allow it due to security concerns. We built Amazon Quick Suite to solve those problems. It’s an agentic AI app that acts as your AI teammate at work – connecting to your business data and apps, and letting you interact with AI agents that can find insights, conduct research, and even take actions across your systems – with the security and privacy enterprises need. Quick works across your existing ecosystem, from emails to Salesforce to Slack to AWS services. You can create custom agents to draft content in your personal style, use Quick Research for in-depth analysis, or set up Quick Flow to automate tasks. And most importantly, your interactions never train the underlying models. We've been testing with Amazon employees and select customers and early results show just how transformational Quick is… cutting analysis time from months to days, and turning week-long tasks into minutes. This is an exciting moment and we're just getting started. Quick is available now, so have at it!

We've all experienced how consumer AI can help in our personal lives, but that same experience hasn't been available at work. Most enterprise data is siloed, consumer AI can't access your work tools, and many orgs won't allow it due to security concerns. We built Amazon Quick Suite to solve those problems. It’s an agentic AI app that acts as your AI teammate at work – connecting to your business data and apps, and letting you interact with AI agents that can find insights, conduct research, and even take actions across your systems – with the security and privacy enterprises need. Quick works across your existing ecosystem, from emails to Salesforce to Slack to AWS services. You can create custom agents to draft content in your personal style, use Quick Research for in-depth analysis, or set up Quick Flow to automate tasks. And most importantly, your interactions never train the underlying models. We've been testing with Amazon employees and select customers and early results show just how transformational Quick is… cutting analysis time from months to days, and turning week-long tasks into minutes. This is an exciting moment and we're just getting started. Quick is available now, so have at it!

Andy Jassy

49,241 次观看 • 10 个月前