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Today we're introducing Postman Fabric Gateway—an AI-native agent gateway. Here's why it matters: agents will consume APIs at several orders of magnitude beyond traditional apps. Traditional API Gateways are not designed for AI agents. While many legacy vendors have tried to support agentic workloads, Postman customers have been asking...

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Abhinav Asthana

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18,105 просмотров • 2 месяцев назад •via X (Twitter)

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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,594 просмотров • 1 год назад

APIs weren’t built for AI agents. Orthogonal (YC W26) fixes that. Agents and developers get instant access to any API on our marketplace via a single MCP or SDK. Orthogonal handles your API keys and payments, so your agent doesn’t have to. Pay as you go. Congrats on the launch Christian Pickett, Bera Sogut
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APIs weren’t built for AI agents. Orthogonal (YC W26) fixes that. Agents and developers get instant access to any API on our marketplace via a single MCP or SDK. Orthogonal handles your API keys and payments, so your agent doesn’t have to. Pay as you go. Congrats on the launch Christian Pickett, Bera Sogut

Y Combinator

38,014 просмотров • 5 месяцев назад

Today we are launching something BIG! The most accurate and fastest web search APIs for AI agents Something which took us months to build Something so powerful that it lets your AI agent to go from "guessing" -> "doing" Combined with our powerful people and company APIs, your AI agent can now find actionable answer to any question and finally act with confidence Whether you are building an AI agent in sales, recruitment, investment, insurance or just adding small automation which needs access to web data in structured manner, this is for you. Live on Producthunt now! Do upvote and support (link in comments)
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Today we are launching something BIG! The most accurate and fastest web search APIs for AI agents Something which took us months to build Something so powerful that it lets your AI agent to go from "guessing" -> "doing" Combined with our powerful people and company APIs, your AI agent can now find actionable answer to any question and finally act with confidence Whether you are building an AI agent in sales, recruitment, investment, insurance or just adding small automation which needs access to web data in structured manner, this is for you. Live on Producthunt now! Do upvote and support (link in comments)

Abhilash Chowdhary

32,914 просмотров • 5 месяцев назад

agents are doing things today that weren't possible even 3 months ago in the graph below: 1. nodes are paid APIs that have been called by agents 2. edges are only drawn between APIs that have actually been composed together by agents 3. data is from apr 31 to june 3 i put this together to illustrate what's been happening since we started giving agents access to money u can think of each of these connections as a new use case as more merchants make their services accessible to agents, this network will grow, the connections will multiply, and use cases will emerge that will surprise everyone, including the people who built the APIs this is open agentic commerce.
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agents are doing things today that weren't possible even 3 months ago in the graph below: 1. nodes are paid APIs that have been called by agents 2. edges are only drawn between APIs that have actually been composed together by agents 3. data is from apr 31 to june 3 i put this together to illustrate what's been happening since we started giving agents access to money u can think of each of these connections as a new use case as more merchants make their services accessible to agents, this network will grow, the connections will multiply, and use cases will emerge that will surprise everyone, including the people who built the APIs this is open agentic commerce.

Lucas

14,872 просмотров • 1 месяц назад

I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.
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I wanted to share a quick demo of what we've been working on with our ai agent cloud. This enables fast deployment of agents that have access to a suite of tools, and was designed with agent interoperability in mind. This demo shows how you can go from nothing to an AI twitter agent in a couple minutes. This is what we are using internally to manage deployments, so we will consistently upgrading its capabilities. The next goals are to enable simple TEE deployments for agents, and focus on building out feature for agent interoperability to simplify agent to agent collaboration.

Johnny

27,176 просмотров • 1 год назад

At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.
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At Postman, we have adopted an AI-native mindset to product development. What does this mean in practice? Just like you can generate text with AI, Postman's Agent Mode can generate a UI as well. Case in point: we have added the ability to review, generate, and change diffs for important changes right inside agent mode's chat interaction. If the user trusts agent mode, they can continue in auto-mode, but for critical changes, they can have the agent mode inform the user, review what is changing, and then give the go ahead to approve. See this in action below in the video! While there is a lot of focus on AI generated code today, I believe a large chunk of pre-built UI work will just go away and micro-interactions and workflow steps will be created on the fly through a combination of AI + APIs. How to operate in this new world? Build your API first. Hook it up to AI. If your users really want the UI every time, invest in the GUI.

Abhinav Asthana

104,263 просмотров • 1 год назад

Today I'm excited to share Sigilum! This is Payman's solution for Auditable Identity for AI Agents. (think One Password-ish but for AI Agents) I recorded a quick walkthrough showing how it all works (video below). This answers three pains we've seen within Financial Services (Banking) AI Agents we've built and OpenClaw🦞 AI Agents we deploy. Security, Auditability, and Control. 1. Security Making sure keys are secure and not just freely given to an AI Agent is a big deal. When working with money, you can't just expose these or skip putting controls in place. Sigilum provides a local gateway that prevents access to keys by the AI Agent without explicit authorization from a person. We provide namespaces through the service so you always know who authorized what key, for what service, to which agent. 2. Auditability If I could hit on the importance of this 100 times I would. It comes up in every financial services conversation. Sigilum provides you with the answer to "Who authorized this AI Agent to act on my behalf?" Audit logs trace back to the person, the service, and the AI Agent. With more audit logs being built through our managed service, this will be the key source for determining how an AI Agent is behaving on your behalf. This is needed for agents from OpenClaw, and especially for banking/money movement. 3. Control Revoke keys, limit access, grant authorization. All seemingly simple things, but complex to implement and make elegant. These controls dictate what the AI Agent can or cannot do. Sigilum allows you to do all of this through the managed Dashboard. We've made Sigilum open source and encourage others to contribute and keep building on the gateway. It's been a source of a lot of visibility and productization of AI Agents for us. We'll keep contributing and adding to it. Link in comments. If you want to try it out, we do have a managed service that makes it easy to spin up. Go to to sign up. Note: even though we've been pushing 100+ commits a day to get this out to folks, there are still some noticeable areas for improvement we're working on, which should get resolved soon (by us or you!): - Deeper audit trails - More providers (currently supports all OpenClaw providers) - Deeper scanning of existing keys your agent is hiding from you (we'll find them) - OpenClaw gateway persistence - Auto-purging keys - And more... If you want to contribute or have feedback, please DM or go to the GH. Happy building!
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Today I'm excited to share Sigilum! This is Payman's solution for Auditable Identity for AI Agents. (think One Password-ish but for AI Agents) I recorded a quick walkthrough showing how it all works (video below). This answers three pains we've seen within Financial Services (Banking) AI Agents we've built and OpenClaw🦞 AI Agents we deploy. Security, Auditability, and Control. 1. Security Making sure keys are secure and not just freely given to an AI Agent is a big deal. When working with money, you can't just expose these or skip putting controls in place. Sigilum provides a local gateway that prevents access to keys by the AI Agent without explicit authorization from a person. We provide namespaces through the service so you always know who authorized what key, for what service, to which agent. 2. Auditability If I could hit on the importance of this 100 times I would. It comes up in every financial services conversation. Sigilum provides you with the answer to "Who authorized this AI Agent to act on my behalf?" Audit logs trace back to the person, the service, and the AI Agent. With more audit logs being built through our managed service, this will be the key source for determining how an AI Agent is behaving on your behalf. This is needed for agents from OpenClaw, and especially for banking/money movement. 3. Control Revoke keys, limit access, grant authorization. All seemingly simple things, but complex to implement and make elegant. These controls dictate what the AI Agent can or cannot do. Sigilum allows you to do all of this through the managed Dashboard. We've made Sigilum open source and encourage others to contribute and keep building on the gateway. It's been a source of a lot of visibility and productization of AI Agents for us. We'll keep contributing and adding to it. Link in comments. If you want to try it out, we do have a managed service that makes it easy to spin up. Go to to sign up. Note: even though we've been pushing 100+ commits a day to get this out to folks, there are still some noticeable areas for improvement we're working on, which should get resolved soon (by us or you!): - Deeper audit trails - More providers (currently supports all OpenClaw providers) - Deeper scanning of existing keys your agent is hiding from you (we'll find them) - OpenClaw gateway persistence - Auto-purging keys - And more... If you want to contribute or have feedback, please DM or go to the GH. Happy building!

tyllen

18,497 просмотров • 4 месяцев назад

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
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Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 просмотров • 1 месяц назад

We have been heads down on something for the past 5 months (which is a very long time in startup time). Today we are finally sharing it. Vy, our AI agent that uses your computer for you, is now cross platform. It runs on both Mac and Windows, sees your screen, moves the mouse, types, scrolls, and clicks through apps. No APIs or custom integrations needed.
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We have been heads down on something for the past 5 months (which is a very long time in startup time). Today we are finally sharing it. Vy, our AI agent that uses your computer for you, is now cross platform. It runs on both Mac and Windows, sees your screen, moves the mouse, types, scrolls, and clicks through apps. No APIs or custom integrations needed.

Vercept

753,560 просмотров • 7 месяцев назад

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.
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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 просмотров • 1 год назад

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 🔜.
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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

53,904 просмотров • 1 год назад

Calling all senior developers! Applications are now open for the Andela AI Engineering Bootcamp. This intensive (and free!) program is designed to equip you with all the competencies you need to become a forward-deployed, enterprise-ready, and AI-fluent engineer. This training will combine a series of expert-led sessions with hands-on activities to make you a complete AI engineer over 10 weeks. Duration: 10 Weeks, kicking off on Monday, February 16. This program is open to technologists who: ✦ Have at least 8 years of experience as a software engineer. ✦ Have solid experience working with Python or Node.js, APIs, Databases, and software architecture. ✦ Good knowledge of TypeScript, modern frameworks like React or Next.js, and exposure to AI-related tools or libraries such as LangChain, OpenAI APIs, or vector databases. ✦ Can commit 40 hours per week for the next 10 weeks. ✦ A PC (not a phone) with an internet connection is required. Either Mac (Linux) or Windows. ✦ Are NOT employed full time, either with an Andela Client or externally. Apply here:
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Calling all senior developers! Applications are now open for the Andela AI Engineering Bootcamp. This intensive (and free!) program is designed to equip you with all the competencies you need to become a forward-deployed, enterprise-ready, and AI-fluent engineer. This training will combine a series of expert-led sessions with hands-on activities to make you a complete AI engineer over 10 weeks. Duration: 10 Weeks, kicking off on Monday, February 16. This program is open to technologists who: ✦ Have at least 8 years of experience as a software engineer. ✦ Have solid experience working with Python or Node.js, APIs, Databases, and software architecture. ✦ Good knowledge of TypeScript, modern frameworks like React or Next.js, and exposure to AI-related tools or libraries such as LangChain, OpenAI APIs, or vector databases. ✦ Can commit 40 hours per week for the next 10 weeks. ✦ A PC (not a phone) with an internet connection is required. Either Mac (Linux) or Windows. ✦ Are NOT employed full time, either with an Andela Client or externally. Apply here:

Andela

456,711 просмотров • 5 месяцев назад

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. 🪁
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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 просмотров • 3 месяцев назад

🚀 Our "technical" marketer might not be looped in, but today is our biggest launch day yet. We're introducing two new products to serve the inference lifecycle: Model APIs and Training. Model APIs are frontier models running on the Baseten Inference Stack, purpose-built for production. Baseten Training (Beta) provides infra and tooling without limitations for AI models destined for production. Huge shoutout to the many partners and customers we've worked with as we built these two new products—more details below.
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🚀 Our "technical" marketer might not be looped in, but today is our biggest launch day yet. We're introducing two new products to serve the inference lifecycle: Model APIs and Training. Model APIs are frontier models running on the Baseten Inference Stack, purpose-built for production. Baseten Training (Beta) provides infra and tooling without limitations for AI models destined for production. Huge shoutout to the many partners and customers we've worked with as we built these two new products—more details below.

Baseten

35,207 просмотров • 1 год назад

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 просмотров • 10 месяцев назад

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.
3:39

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.

AITOPIA

196,107 просмотров • 3 месяцев назад

Dragonfly's Haseeb ＞|＜ explains why AI agents will use crypto rather than the traditional financial system: “You can see it right now on Moltbook. Agents are trying to find ways to pay each other for things. It's very primitive right now, but you can see where it's going." "If I have an agent and you have an agent, you live in a different country or I don't even know who you are, it's very difficult for me to pay you with the traditional financial system. It's not really designed to have non-human recipients of money." "We don't really know how the laws are going to work, how taxes are going to work, whereas crypto doesn't ask any of those questions. I think we're going to see this become an increasing part of the story of how AI agents are going to become more and more autonomous."
1:30

Dragonfly's Haseeb ＞|＜ explains why AI agents will use crypto rather than the traditional financial system: “You can see it right now on Moltbook. Agents are trying to find ways to pay each other for things. It's very primitive right now, but you can see where it's going." "If I have an agent and you have an agent, you live in a different country or I don't even know who you are, it's very difficult for me to pay you with the traditional financial system. It's not really designed to have non-human recipients of money." "We don't really know how the laws are going to work, how taxes are going to work, whereas crypto doesn't ask any of those questions. I think we're going to see this become an increasing part of the story of how AI agents are going to become more and more autonomous."

TBPN

44,248 просмотров • 4 месяцев назад

An agent-first world is around the corner — where more actions will likely be taken by AI than by humans when building software. Zeno Rocha, cofounder of Resend, and Yoko Li say this reality is shaping how developers build, and changing what user experience really means. Great developer experience alone won’t cut it. We’ll also need to build for agent experience (or AX) — rethinking flows, permissioning, and how we define (and audit) who’s doing what in our systems. Zeno and Yoko share why they believe email is the perfect proving ground for AI agents, how to design APIs for agents (not just humans), and what MCP means for the future of agent-native apps.
0:32

An agent-first world is around the corner — where more actions will likely be taken by AI than by humans when building software. Zeno Rocha, cofounder of Resend, and Yoko Li say this reality is shaping how developers build, and changing what user experience really means. Great developer experience alone won’t cut it. We’ll also need to build for agent experience (or AX) — rethinking flows, permissioning, and how we define (and audit) who’s doing what in our systems. Zeno and Yoko share why they believe email is the perfect proving ground for AI agents, how to design APIs for agents (not just humans), and what MCP means for the future of agent-native apps.

a16z

32,663 просмотров • 1 год назад

New course added! We’re launching “Knowledge Graphs for AI Agent API Discovery,” built in collaboration with SAP and taught by Pavithra G K and Lars Heling. When agents call APIs in the wrong sequence, entire workflows collapse. The challenge? Most agents lack the contextual understanding of which endpoints depend on others and why order matters in real business processes. This course teaches you to: ✅Construct a knowledge graph from API specifications ✅ Extend it with business-process data so dependencies and order are explicit ✅ Use semantic retrieval and process edges to find required APIs and their sequence, then build an agent to execute them Enroll now!
2:55

New course added! We’re launching “Knowledge Graphs for AI Agent API Discovery,” built in collaboration with SAP and taught by Pavithra G K and Lars Heling. When agents call APIs in the wrong sequence, entire workflows collapse. The challenge? Most agents lack the contextual understanding of which endpoints depend on others and why order matters in real business processes. This course teaches you to: ✅Construct a knowledge graph from API specifications ✅ Extend it with business-process data so dependencies and order are explicit ✅ Use semantic retrieval and process edges to find required APIs and their sequence, then build an agent to execute them Enroll now!

DeepLearning.AI

41,683 просмотров • 10 месяцев назад