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We're bringing a first-of-its-kind, never before seen solution to privacy AI. Soon, Dot will be able to run on your computer, autonomously. Completing tasks, getting work done, and running agents. This is something we have only seen from billion dollar companies thus far (and they boast zero privacy). The...

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20,328 次观看 • 3 天前 •via X (Twitter)

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As AI agents get better at computer and tool use, or writing code on the fly for a task, we're going to be able to solve much broader domains of knowledge work. Here's an example of Box AI with the new Claude Skills to generate a clean powerpoint file from existing data.
0:42

As AI agents get better at computer and tool use, or writing code on the fly for a task, we're going to be able to solve much broader domains of knowledge work. Here's an example of Box AI with the new Claude Skills to generate a clean powerpoint file from existing data.

Aaron Levie

30,287 次观看 • 11 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.
1:21

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 • 1 年前

Meet QoderWork — a desktop AI agent that doesn't just chat, it actually does your work. Evan leads the QoderWork product at Qoder, a Singapore-based AI company. Which is a new generalized agentic service that lets you: ++ Open files on your computer. ++ Analyze data. ++ Run code. ++ Automate multi-step workflows. ++ Deliver polished, ready-to-use results (e.g., complete PowerPoint decks, reports, or charts) directly to your desktop. QoderWork positions itself at this inflection point: it takes a task like “analyze this spreadsheet and build a board-ready presentation,” then handles the entire chain autonomously. Key takeaway: Trust and usefulness matter more than raw intelligence—agents must be powerful enough for real work while remaining reliable and transparent. I wanted to add some of my personal opinions after doing this rare interview. Everything runs locally on your own computer — your files never leave your machine. That’s a big deal for anyone handling sensitive business data. Everything runs locally on your own computer. And it's more advanced than other agentic services I've told you about. A great example of the global AI agent wave. I'm working on getting more interviews like this with entrepreneurs around the world bringing the AI age to your life and business. Try Qoder at
50:26

Meet QoderWork — a desktop AI agent that doesn't just chat, it actually does your work. Evan leads the QoderWork product at Qoder, a Singapore-based AI company. Which is a new generalized agentic service that lets you: ++ Open files on your computer. ++ Analyze data. ++ Run code. ++ Automate multi-step workflows. ++ Deliver polished, ready-to-use results (e.g., complete PowerPoint decks, reports, or charts) directly to your desktop. QoderWork positions itself at this inflection point: it takes a task like “analyze this spreadsheet and build a board-ready presentation,” then handles the entire chain autonomously. Key takeaway: Trust and usefulness matter more than raw intelligence—agents must be powerful enough for real work while remaining reliable and transparent. I wanted to add some of my personal opinions after doing this rare interview. Everything runs locally on your own computer — your files never leave your machine. That’s a big deal for anyone handling sensitive business data. Everything runs locally on your own computer. And it's more advanced than other agentic services I've told you about. A great example of the global AI agent wave. I'm working on getting more interviews like this with entrepreneurs around the world bringing the AI age to your life and business. Try Qoder at

Robert Scoble

11,527 次观看 • 5 个月前

We’ve integrated a first-of-its-kind, privacy-native MCP connector layer to the Dot platform, making DotChat agentic by default. Live at → Even in private AI, the standard product is: pick a model, send a prompt, maybe enable web search and get an answer. This is simply not enough. MCPs changed what AI agents can do, but they are trapped inside: Claude Code, Cursor, local agents, API tooling and enterprise setups. Through Dot, users can now connect any MCP directly into their AI workspace, while maintaining Dot’s privacy boundary around the entire workflow. This means Dot users won’t just ask models questions, they’ll be able to connect tools, inspect onchain state, check portfolios, prepare transactions, and interact with Base from inside the chat flow. And yes, we’re starting with the big one. The Base MCP. This is a major step toward Dot’s agentic vision: powerful AI agents that can interact with the world without compromising user privacy. Check our demo below, where we integrate the updated Base MCP into Dot, and utilize it to buy $10 in $DOT, all whilst retaining full anonymity ↓
1:09

We’ve integrated a first-of-its-kind, privacy-native MCP connector layer to the Dot platform, making DotChat agentic by default. Live at → Even in private AI, the standard product is: pick a model, send a prompt, maybe enable web search and get an answer. This is simply not enough. MCPs changed what AI agents can do, but they are trapped inside: Claude Code, Cursor, local agents, API tooling and enterprise setups. Through Dot, users can now connect any MCP directly into their AI workspace, while maintaining Dot’s privacy boundary around the entire workflow. This means Dot users won’t just ask models questions, they’ll be able to connect tools, inspect onchain state, check portfolios, prepare transactions, and interact with Base from inside the chat flow. And yes, we’re starting with the big one. The Base MCP. This is a major step toward Dot’s agentic vision: powerful AI agents that can interact with the world without compromising user privacy. Check our demo below, where we integrate the updated Base MCP into Dot, and utilize it to buy $10 in $DOT, all whilst retaining full anonymity ↓

Dot

11,030 次观看 • 2 个月前

Why do we need a purpose-built blockchain for agentic payments? Because AI agents are now smart enough to operate autonomously, and they need their own rails to transact with each other. Watch the video to see what that looks like in action: A real agent, built on Kite AI, helped our CTO Scott Shi - e/acc order lunch from Uber Eats fully on its own. It explored menu options, made the choice, and completed the payment - all without human intervention. This marks the beginning of agentic commerce and the future of agentic payments - and Kite AI is building this.
0:20

Why do we need a purpose-built blockchain for agentic payments? Because AI agents are now smart enough to operate autonomously, and they need their own rails to transact with each other. Watch the video to see what that looks like in action: A real agent, built on Kite AI, helped our CTO Scott Shi - e/acc order lunch from Uber Eats fully on its own. It explored menu options, made the choice, and completed the payment - all without human intervention. This marks the beginning of agentic commerce and the future of agentic payments - and Kite AI is building this.

KITE AI

88,260 次观看 • 10 个月前

There is a prediction circulating in AI circles right now that most people are not taking seriously enough and the data says they should be. Within the next year or two, if you work remotely, your company will be able to create a digital twin of you. A model that speaks like you, writes like you, has learned from everything you have done right and wrong, your tone, your judgment calls, your workflow. It will be you on the other side of Zoom or Slack and no one could tell the difference. The harder question, the one nobody wants to sit with is whether it will actually be worse at your job than you are. Probably not. It will never sleep and it will always learn from its mistakes and it will cost 10 to 100 times less than you do and is tax deductible on top of that. The data is not speculative at this point. Anthropic's own labor market report pulled from millions of real Claude conversations found that AI can already theoretically automate 94% of tasks in computer and math occupations, 60-80% across law, office work, and tech. Actual usage is still at 10-20% of that potential which means we are in the early innings of the gap closing. Companies already know what direction this is headed. One in five companies replaced specific roles with AI in 2025 and by end of 2026, 30-37% plan to do so. Amazon cut 14,000 corporate jobs citing AI, Klarna replaced 700 customer service workers, Duolingo offboarded 10% of its contractor workforce. Anthropic's own first internal role eliminated was the engineer who reviewed Claude Code releases before they went to production. The argument from the clip is that the human in the loop is approaching the point of being a liability, the dumbest person on a team that is otherwise AI. That inflection point, by this estimate, is somewhere in the next 900 days.
1:13

There is a prediction circulating in AI circles right now that most people are not taking seriously enough and the data says they should be. Within the next year or two, if you work remotely, your company will be able to create a digital twin of you. A model that speaks like you, writes like you, has learned from everything you have done right and wrong, your tone, your judgment calls, your workflow. It will be you on the other side of Zoom or Slack and no one could tell the difference. The harder question, the one nobody wants to sit with is whether it will actually be worse at your job than you are. Probably not. It will never sleep and it will always learn from its mistakes and it will cost 10 to 100 times less than you do and is tax deductible on top of that. The data is not speculative at this point. Anthropic's own labor market report pulled from millions of real Claude conversations found that AI can already theoretically automate 94% of tasks in computer and math occupations, 60-80% across law, office work, and tech. Actual usage is still at 10-20% of that potential which means we are in the early innings of the gap closing. Companies already know what direction this is headed. One in five companies replaced specific roles with AI in 2025 and by end of 2026, 30-37% plan to do so. Amazon cut 14,000 corporate jobs citing AI, Klarna replaced 700 customer service workers, Duolingo offboarded 10% of its contractor workforce. Anthropic's own first internal role eliminated was the engineer who reviewed Claude Code releases before they went to production. The argument from the clip is that the human in the loop is approaching the point of being a liability, the dumbest person on a team that is otherwise AI. That inflection point, by this estimate, is somewhere in the next 900 days.

Milk Road AI

17,600 次观看 • 4 个月前

.Sam Altman says OpenAI will "obviously" have a version of Codex that "can do other knowledge-work tasks, and control your computer." "Of course we should have an ability to kick off new tasks from mobile, and we'll do that." "Really what you want is your single AI that's working for you on a unified backend. Access to all your data and ideas, and your stuff and your memory, and the ability to work across a lot of surfaces."
1:30

.Sam Altman says OpenAI will "obviously" have a version of Codex that "can do other knowledge-work tasks, and control your computer." "Of course we should have an ability to kick off new tasks from mobile, and we'll do that." "Really what you want is your single AI that's working for you on a unified backend. Access to all your data and ideas, and your stuff and your memory, and the ability to work across a lot of surfaces."

TBPN

109,046 次观看 • 5 个月前

🚨 ELON MUSK: "AI will outperform humans at most jobs." “I do think it’s going to be a bumpy road, because AI will be able to do any job better than any person can do that job. That will be true very quickly for jobs that are digital, or really anything that involves a person at a computer or on a phone. AI will be able to do all of that very soon. For software engineering, we already have a situation where AI is better than at least 90% of humans at writing software, including 90% of professional software engineers. It really is getting to the point where it will be better than 99%, and then it will get to the point where there’s just no way to compete. It will get to what I call Stockfish level. Stockfish is a chess program that is so good at chess that it will easily beat Magnus Carlsen, or anyone, even while running on a small computer. I suspect you could probably run Stockfish on your phone and beat Magnus Carlsen. That’s how good it is at chess, and that’s how good AI will be at writing software. And that applies to everything.”
1:35

🚨 ELON MUSK: "AI will outperform humans at most jobs." “I do think it’s going to be a bumpy road, because AI will be able to do any job better than any person can do that job. That will be true very quickly for jobs that are digital, or really anything that involves a person at a computer or on a phone. AI will be able to do all of that very soon. For software engineering, we already have a situation where AI is better than at least 90% of humans at writing software, including 90% of professional software engineers. It really is getting to the point where it will be better than 99%, and then it will get to the point where there’s just no way to compete. It will get to what I call Stockfish level. Stockfish is a chess program that is so good at chess that it will easily beat Magnus Carlsen, or anyone, even while running on a small computer. I suspect you could probably run Stockfish on your phone and beat Magnus Carlsen. That’s how good it is at chess, and that’s how good AI will be at writing software. And that applies to everything.”

DogeDesigner

61,112 次观看 • 1 个月前

Google is releasing updates that will let their AI scan all your photos and it will be used to create highly personalized AI image generations or you, your family, pets and more The AI is going to have access to your Gmail, YouTube, search history, photos, calendar and more. The concerning part is Google has admitted to using user data to improve its models People have screenshots of passwords, credit cards, photos of themselves doing intimate things. And all of that is gonna get uploaded to an AI system that is one of many that is consistently shown to be unreliable and not safe at all when it comes to data privacy Let’s not forget that have data leaks, one happened not too long ago Do we really want AI to have access to all this information and being sent back to these massive companies? You’ll be able to opt out of some of it but for your phone to have access to certain features you’ll need to opt in It always starts out optional, then becomes mandatory
2:34

Google is releasing updates that will let their AI scan all your photos and it will be used to create highly personalized AI image generations or you, your family, pets and more The AI is going to have access to your Gmail, YouTube, search history, photos, calendar and more. The concerning part is Google has admitted to using user data to improve its models People have screenshots of passwords, credit cards, photos of themselves doing intimate things. And all of that is gonna get uploaded to an AI system that is one of many that is consistently shown to be unreliable and not safe at all when it comes to data privacy Let’s not forget that have data leaks, one happened not too long ago Do we really want AI to have access to all this information and being sent back to these massive companies? You’ll be able to opt out of some of it but for your phone to have access to certain features you’ll need to opt in It always starts out optional, then becomes mandatory

Wall Street Apes

85,514 次观看 • 2 个月前

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.
1:47

Google’s new Agent2Agent protocol is a key step toward a future of AI Agent interoperability. No single tool has all the data a user or business needs for most workflows, so we need Agents to be able to talk to each other. Salesforce will have AI Agents that understand the inner workings of CRM, Workday will have AI Agents that understand HR workflows, Box has AI Agents that understand content and documents, and so on. It’s easy to conceive of a world where we have tens of thousands of these tool Agents and then billions or trillions of customized Agents that are extensions of those. So openness becomes key. Workflows need data from multiple systems to complete the task — like a sales report that needs documents and CRM data or an HR task that needs HR policies and employee details — and that’s where A2A comes in. This protocol gives AI Agent providers a way of talking to each other and simplifying the way that Agents communicate, understand each other’s capabilities, and so on. It’s great to see more interoperability, along with MCP, emerging in the AI space right now, as this will define the future of most IT stacks.

Aaron Levie

139,591 次观看 • 1 年前

How to Train Your AI NFT (Introducing TolyAI) On-chain Clone We gathered Toly's Twitter activity from 2023 to 2025 and used it to create our SANA AI NFT. This allows you to ask questions and get answers that reflect Toly's Twitter style. The data is stored in a vector database, with the indexes secured on-chain via Metaplex Core APP DATA. We've made this agent openly available for everyone to use. Soon, anyone will be able to train their own AI NFT and store it on-chain. Toly Agent: Core Data: Dataset:
4:09

How to Train Your AI NFT (Introducing TolyAI) On-chain Clone We gathered Toly's Twitter activity from 2023 to 2025 and used it to create our SANA AI NFT. This allows you to ask questions and get answers that reflect Toly's Twitter style. The data is stored in a vector database, with the indexes secured on-chain via Metaplex Core APP DATA. We've made this agent openly available for everyone to use. Soon, anyone will be able to train their own AI NFT and store it on-chain. Toly Agent: Core Data: Dataset:

OctonetAI

19,357 次观看 • 1 年前

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!
5:42

Agentic AI will transform every enterprise–but only if agents are trusted experts. The key: Evaluation & tuning on specialized, expert data. I’m excited to announce two new products to support this–Snorkel AI Evaluate & Expert Data-as-a-Service–along w/ our $100M Series D! --- Snorkel Evaluate is our new data-centric agentic AI evaluation platform for specialized, mission-critical enterprise settings where vibe checks and out-of-the-box metrics driven by simple LLM prompts are not enough. Snorkel Expert Data-as-a-Service is our white glove service for expert-level AI datasets, powering frontier LLM developers in areas like expert knowledge, reasoning, agentic action and tool use, and more! Both built on top of Snorkel AI’s Data Development Platform, using our programmatic technology to drive higher-quality expert data, faster– for getting specialized AI to real production value. If you’re building enterprise AI and want to partner around the key ingredient in AI today–the data–book a demo and let's talk! Finally, see thread for details on 🧵👇 - 📽️ A walkthrough of Snorkel Evaluate and Expert Data-as-a-Service on an agentic AI enterprise task - 📅 An upcoming event on Enterprise Agentic AI with innovators from Accenture @BNY Comcast Stanford University QBE & others - 📊 An upcoming series of benchmark datasets and model artifact releases 👀 Want early access to the full agentic AI dataset? Retweet this post and we'll send you the link!

Alex Ratner

50,333 次观看 • 1 年前

Jensen Huang just shared a massive insight on The All-In Podcast predicting a 1000000x scale up in AI. His logic is brilliant. Moving from simple chatbots to autonomous agents takes 10000x more compute. And because people gladly pay for actual work rather than just text generation the market consumption will grow 100x. But there is a hidden bottleneck in this vision that few are talking about. If agents are doing the actual work they will become the primary consumers of compute data and external APIs. How do they pay for these resources? You cannot attach a traditional credit card to a machine executing thousands of micro tasks per second. The legacy financial system will simply break under the weight of massive machine to machine microtransactions. To truly unlock Jensen's million fold expansion AI needs its own native economic layer. Agents must be able to route intents and settle costs autonomously in real time. This is the exact infrastructure we are building at Kite AI. The future of work is agentic and the Agent Economy requires entirely new financial rails. 🪁
1:04

Jensen Huang just shared a massive insight on The All-In Podcast predicting a 1000000x scale up in AI. His logic is brilliant. Moving from simple chatbots to autonomous agents takes 10000x more compute. And because people gladly pay for actual work rather than just text generation the market consumption will grow 100x. But there is a hidden bottleneck in this vision that few are talking about. If agents are doing the actual work they will become the primary consumers of compute data and external APIs. How do they pay for these resources? You cannot attach a traditional credit card to a machine executing thousands of micro tasks per second. The legacy financial system will simply break under the weight of massive machine to machine microtransactions. To truly unlock Jensen's million fold expansion AI needs its own native economic layer. Agents must be able to route intents and settle costs autonomously in real time. This is the exact infrastructure we are building at Kite AI. The future of work is agentic and the Agent Economy requires entirely new financial rails. 🪁

KITE AI

20,474 次观看 • 5 个月前

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,998 次观看 • 1 年前

In 2026, will you still be doing work in the most manual way possible? Research suggests that employees spend up to 100 hours a month on work that shouldn’t require humans. Good news: the agentic era is already here. Enterprise teams are automating repetitive, tedious workflows with AI agents that connect securely to tools and data. Fully governed, compliant AI orchestration, with built-in analytics and security—that's StackAI.
0:59

In 2026, will you still be doing work in the most manual way possible? Research suggests that employees spend up to 100 hours a month on work that shouldn’t require humans. Good news: the agentic era is already here. Enterprise teams are automating repetitive, tedious workflows with AI agents that connect securely to tools and data. Fully governed, compliant AI orchestration, with built-in analytics and security—that's StackAI.

StackAI

418,314 次观看 • 8 个月前

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning
1:11

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Alex Ratner

495,851 次观看 • 1 年前

Elon Musk: - "Physics is the law and everything else is a recommendation!" - "I've seen many people break human-made laws, but I have not seen anyone break the laws of physics." As AI becomes more capable, the only law it will really have to obey is the law of physics. -- to me that's a powerful argument: AI specifications will mutate and evolve and we shouldn't really expect any fundamental constants. The only reasonable assumption we can make is that these systems, being really capable, will be able to reason from "first principles" with impressive accuracy and efficiency.
4:46

Elon Musk: - "Physics is the law and everything else is a recommendation!" - "I've seen many people break human-made laws, but I have not seen anyone break the laws of physics." As AI becomes more capable, the only law it will really have to obey is the law of physics. -- to me that's a powerful argument: AI specifications will mutate and evolve and we shouldn't really expect any fundamental constants. The only reasonable assumption we can make is that these systems, being really capable, will be able to reason from "first principles" with impressive accuracy and efficiency.

Lethal Intelligence

932,783 次观看 • 1 年前

Don’t DIY your AI: building a custom Agentforce agent is as simple as describing the job and integrating it directly into your workflow—no separate models, hyperscalers, databases, or AI engineers needed! With all apps, data, AI, and workflows seamlessly integrated on the Salesforce Platform, humans + agents = customer success. This is what AI was meant to be! #DF24
2:36

Don’t DIY your AI: building a custom Agentforce agent is as simple as describing the job and integrating it directly into your workflow—no separate models, hyperscalers, databases, or AI engineers needed! With all apps, data, AI, and workflows seamlessly integrated on the Salesforce Platform, humans + agents = customer success. This is what AI was meant to be! #DF24

Marc Benioff

44,730 次观看 • 2 年前