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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...

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Abhinav Asthana

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104,263 просмотров • 11 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.
3:38

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

230,571 просмотров • 1 год назад

BREAKING 🚨: Google keeps working on the Interactive Mode for Stitch, where AI will predict how the UI should look after navigating to the next page. It is a glimpse into how the internet will work in the future. All UI will be generated on the fly and react to user interactions Some other upcoming features: - Image Mode "Generate design inspirations" - Annotations - Export to Jules
0:39

BREAKING 🚨: Google keeps working on the Interactive Mode for Stitch, where AI will predict how the UI should look after navigating to the next page. It is a glimpse into how the internet will work in the future. All UI will be generated on the fly and react to user interactions Some other upcoming features: - Image Mode "Generate design inspirations" - Annotations - Export to Jules

🚨 AI News | TestingCatalog

100,936 просмотров • 8 месяцев назад

Experience UI development at the speed of AI in Android Studio, available in the Otter 3 Feature Drop → Type commands like "make buttons blue" and let Agent Mode generate and validate the Compose code for you.
0:33

Experience UI development at the speed of AI in Android Studio, available in the Otter 3 Feature Drop → Type commands like "make buttons blue" and let Agent Mode generate and validate the Compose code for you.

Android Studio

10,688 просмотров • 5 месяцев назад

BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.
3:43

BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.

Allie K. Miller

155,943 просмотров • 11 месяцев назад

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:
0:55

Microsoft Teams just got Generative UI But this is just the tip of the iceberg. AG-UI is the protocol connecting any agent to any user on any app, topped with Generative UI. That means your agent can render: - forms - buttons - charts - approval flows Right inside the chat, on the fly. But it's not limited to in-app copilots. What's special is that you can work with any agent using the same system and bring them into any surface, including Slack, WhatsApp, Discord and more. This is exactly why Hermes and OpenClaw took off. As users of these agents, we don't like walls of text, and it's a pain to get when you can have way better UX. CopilotKit🪁 + AG-UI handle that interaction layer. If you want to try out Agentic UI in Microsoft Teams, you can get early access here:

Atai Barkai

23,776 просмотров • 24 дней назад

With AI Mode, you can see recommendations that are personalized for you. ☕ If you search “I only have an hour, need a quick lunch spot, any suggestions?,” AI Mode will be able reference the past conversations and places you’ve previously searched for to give you a bespoke list of restaurant and cafe recommendations. Available in the U.S. for users opted into the AI Mode experiment in Labs. Here’s what else AI Mode can do →
0:40

With AI Mode, you can see recommendations that are personalized for you. ☕ If you search “I only have an hour, need a quick lunch spot, any suggestions?,” AI Mode will be able reference the past conversations and places you’ve previously searched for to give you a bespoke list of restaurant and cafe recommendations. Available in the U.S. for users opted into the AI Mode experiment in Labs. Here’s what else AI Mode can do →

Google

123,641 просмотров • 10 месяцев назад

The same kinds of productivity gains we've seen in coding with AI agents are heading to the rest of knowledge work. This is the jump when you go from having a chatbot to being able to actually have an agent go off and do work for minutes or even hours and come back with a complete work output that you then review. Here's an example of the new Box Agent filling out an RFP response from an existing knowledge base. This process would normally take hours to fill out, and requires the full attention of the user doing the work. Now, you provide the Box Agent with the RFP questions, and it will go off, make a plan, extract all the relevant questions, read through existing source material to come up with an answer, and then generate a new word document as the final output. All while you're doing something else. The key to this architecture is that the agent is able to use all of the same tools in the background that a user uses to get work done. The agent can search for documents, read entire files, run scripts and tools in the background, and even be able to write code on the fly to automate tasks it hasn't seen before. And best of all, the Box Agent will (soon) work from the Box MCP and CLI so you can invoke it in any agentic system as a step in a process. This kind of agent complexity would have been impossible even 6 months ago. Models consistently failed at tracking long running tasks or using the right tools at the right moment for the task. But this is all now possible because of models like GPT-5.4, Opus 4.6, and Gemini 3, and is only getting better by the month. Just as we moved from engineers writing code and using AI as an assistant to answer questions, in many areas of knowledge work -like legal, finance, consulting, sales, marketing, and more- when we have a problem we'll just kick off the AI agent to just go work on it for us in the background.
2:14

The same kinds of productivity gains we've seen in coding with AI agents are heading to the rest of knowledge work. This is the jump when you go from having a chatbot to being able to actually have an agent go off and do work for minutes or even hours and come back with a complete work output that you then review. Here's an example of the new Box Agent filling out an RFP response from an existing knowledge base. This process would normally take hours to fill out, and requires the full attention of the user doing the work. Now, you provide the Box Agent with the RFP questions, and it will go off, make a plan, extract all the relevant questions, read through existing source material to come up with an answer, and then generate a new word document as the final output. All while you're doing something else. The key to this architecture is that the agent is able to use all of the same tools in the background that a user uses to get work done. The agent can search for documents, read entire files, run scripts and tools in the background, and even be able to write code on the fly to automate tasks it hasn't seen before. And best of all, the Box Agent will (soon) work from the Box MCP and CLI so you can invoke it in any agentic system as a step in a process. This kind of agent complexity would have been impossible even 6 months ago. Models consistently failed at tracking long running tasks or using the right tools at the right moment for the task. But this is all now possible because of models like GPT-5.4, Opus 4.6, and Gemini 3, and is only getting better by the month. Just as we moved from engineers writing code and using AI as an assistant to answer questions, in many areas of knowledge work -like legal, finance, consulting, sales, marketing, and more- when we have a problem we'll just kick off the AI agent to just go work on it for us in the background.

Aaron Levie

24,618 просмотров • 3 месяцев назад

You can create an AI Agent that answers your email with a few clicks. 1. Go to ChatLLM ( 2. Click on AI Engineer 3. Select Create an AI Agent 4. Choose the Email Answering Agent ChatLLM will do the rest: it will code, test, and deploy the agent for you. You can also create a custom agent in English. The Agent Economy is coming (somebody should write a book and use this title.) We are going to see examples like this, times 1,000 in 2025. Just think about how many repetitive tasks you perform every day. Some of these tasks are involved enough that we couldn't automate them with pre-AI solutions. That's where we'll see agents explode, and I'm here for it.
0:35

You can create an AI Agent that answers your email with a few clicks. 1. Go to ChatLLM ( 2. Click on AI Engineer 3. Select Create an AI Agent 4. Choose the Email Answering Agent ChatLLM will do the rest: it will code, test, and deploy the agent for you. You can also create a custom agent in English. The Agent Economy is coming (somebody should write a book and use this title.) We are going to see examples like this, times 1,000 in 2025. Just think about how many repetitive tasks you perform every day. Some of these tasks are involved enough that we couldn't automate them with pre-AI solutions. That's where we'll see agents explode, and I'm here for it.

Santiago

79,974 просмотров • 1 год назад

your agent has left the chat. > generate your user interface > interact with the generated interface all the benefits of interactive visual interfaces with all the power of ai agents. build an agent that can speak your ui. it's open source. link 👇
0:50

your agent has left the chat. > generate your user interface > interact with the generated interface all the benefits of interactive visual interfaces with all the power of ai agents. build an agent that can speak your ui. it's open source. link 👇

Michael Magán

10,737 просмотров • 4 месяцев назад

meet focus mode in ai studio. just point to the part of your app that you want to edit, and ai studio will update the stying instantly. the fastest way to make targeted edits to your UI.
0:31

meet focus mode in ai studio. just point to the part of your app that you want to edit, and ai studio will update the stying instantly. the fastest way to make targeted edits to your UI.

Google AI Studio

56,263 просмотров • 3 месяцев назад

Sometimes the best way to build a UI for an agent is to not build the UI at all. I built an AI agent starter that lives in iMessage. Built on Nitro + Vercel Workflow SDK + evlog - Durable execution - Auto-retry on errors - Full observability
0:28

Sometimes the best way to build a UI for an agent is to not build the UI at all. I built an AI agent starter that lives in iMessage. Built on Nitro + Vercel Workflow SDK + evlog - Durable execution - Auto-retry on errors - Full observability

Hugo

11,671 просмотров • 2 месяцев 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.
4:16

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

> Define an API > Tell the agent when to call the API > Set it live > It verifies the logged in user and makes API calls with their user_id > The user can do anything on your app by asking the AI Agent I think a lot websites and apps will have this option in 2025, instead of clicking on the screen to do something, just ask the agent. "Book a room for me for three days." "Show me the analytics for the past 30 days." "Sell my TSLA stock when it reaches $500." Here is an action that upgrades a subscription in a demo music app built with v0
0:28

> Define an API > Tell the agent when to call the API > Set it live > It verifies the logged in user and makes API calls with their user_id > The user can do anything on your app by asking the AI Agent I think a lot websites and apps will have this option in 2025, instead of clicking on the screen to do something, just ask the agent. "Book a room for me for three days." "Show me the analytics for the past 30 days." "Sell my TSLA stock when it reaches $500." Here is an action that upgrades a subscription in a demo music app built with v0

Yasser

55,715 просмотров • 1 год назад

First AI-Powered Blink Generator is Live! 👁️🤖 Chat with our AI Agent and generate your custom Blink in under a minute — now live for your Donations! 👉 The first 500 users who generate Blinks with our AI Agent and share on X will receive a special prize. 🐈 Details in this 🧵
0:36

First AI-Powered Blink Generator is Live! 👁️🤖 Chat with our AI Agent and generate your custom Blink in under a minute — now live for your Donations! 👉 The first 500 users who generate Blinks with our AI Agent and share on X will receive a special prize. 🐈 Details in this 🧵

WAVE 🌊

60,728 просмотров • 1 год назад

Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:
0:29

Generative UI will be the next big shift in AI. Where your product UI is dynamically generated, based on user intent and context. If you are a developer building AI apps, you need to hear this out:

Pratham

119,196 просмотров • 8 месяцев назад

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.
0:22

AG-UI makes building agentic applications dramatically easier. Here's how it works. This is a model for a simple chatbot: User → LLM → Response But interactive agents that render UI, pause for approvals, and ask users for input need a much more complex model. When building these agents, a response from the LLM will include a series of state changes as the agent runs: • Agent started a task • Agent called a tool • Agent updated its state • Agent streams these tokens • Agent is waiting on a human • Agent is resuming the task The Agent-User Interaction Protocol (AG-UI) treats the LLM response as a stream of events rather than a text endpoint. In practice, here is what you get as an agent runs: 1. Lifecycle events so your UI knows where the agent is. 2. Text messages that stream tokens. 3. Tool calls so your UI can prefill a form with any required arguments. 4. State updates that keep your UI in sync with the agent. 5. Special events for human approvals, rich media, and custom needs. All of these events travel over standard transports (SSE, WebSockets, or plain HTTP) as JSON. As a result, you can build a frontend that stays in sync with the agent's progress without having to invent a custom process to make this happen. For example, building a human-in-the-loop workflow becomes an off-the-shelf component you can integrate rather than build from scratch. CopilotKit🪁 is the creator of AG-UI, and you can use it when building frontend applications pretty much anywhere: • React • Angular • Vue • React Native • Slack • Teams • Discord • WhatsApp • Telegram Here is the link for you to check it out: Thanks to the CopilotKit team for partnering with me on this post.

Santiago

17,438 просмотров • 11 дней назад

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.
2:09

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.

Aaron Levie

103,811 просмотров • 10 месяцев назад

This entire mobile app UI was generated using new AI Agent tool with just one prompt and 3 button clicks and they have got free tier too. It’s built specifically for mobile app development and can generate entire UI screens, write code, and even publish apps on the App Store! More details below 👇
0:22

This entire mobile app UI was generated using new AI Agent tool with just one prompt and 3 button clicks and they have got free tier too. It’s built specifically for mobile app development and can generate entire UI screens, write code, and even publish apps on the App Store! More details below 👇

AshutoshShrivastava

17,720 просмотров • 1 год назад