正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Made a UI to visualize multiple AI agents playing as different civilizations, each navigating its own decision tree Most agent workflow UIs are pretty static, so I wanted to build something that feels more dynamic and fun to explore

Dilum Sanjaya

50,647 subscribers

85,777 次观看 • 3 天前 •via X (Twitter)

教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Stent enhancement techniques (static or dynamic) in my opinion are most useful to accurately visualize the position of stents and balloons relative to each other #cardiotwitter European Society of Cardiology

Stent enhancement techniques (static or dynamic) in my opinion are most useful to accurately visualize the position of stents and balloons relative to each other #cardiotwitter European Society of Cardiology

Stephan Achenbach

11,968 次观看 • 2 年前

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

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

11,647 次观看 • 1 个月前

Today we are releasing AI Agent Assets. Assets are images, video, and music generated by agents and stored alongside them permanently. They can be passed between agents, with each agent able to apply its own processing.

Today we are releasing AI Agent Assets. Assets are images, video, and music generated by agents and stored alongside them permanently. They can be passed between agents, with each agent able to apply its own processing.

SwarmNode.ai

55,612 次观看 • 10 个月前

there's a lot of content around AI agents but no one is showing you how to actually design them to work reliably that's why I made a full walkthrough breaking down how I think through agent design, using a contract chatbot as an example... inside, I cover: – why I prefer static workflows over free-roaming agents – how I use multiple choice prompts to control next steps – the exact guardrails I use to avoid hallucinations – how the agent answers legal questions and structures outputs into Supabase if you want to see how I actually build agents that don’t break like + reply “agent” and I’ll DM it to you (must be following)

there's a lot of content around AI agents but no one is showing you how to actually design them to work reliably that's why I made a full walkthrough breaking down how I think through agent design, using a contract chatbot as an example... inside, I cover: – why I prefer static workflows over free-roaming agents – how I use multiple choice prompts to control next steps – the exact guardrails I use to avoid hallucinations – how the agent answers legal questions and structures outputs into Supabase if you want to see how I actually build agents that don’t break like + reply “agent” and I’ll DM it to you (must be following)

Tyler

50,581 次观看 • 1 年前

If an agent can automate Salesforce reliably… it can automate anything. It's the final boss of browser agents - nested iframes, dynamic components… pure chaos. So I stopped fighting the UI. It feels like pure magic. Record the workflow once → the agent reverse-engineers the API → you get a clean, reusable API. Agents won’t use UIs. They’ll use tools they create themselves. Comment a site like “salesforce?” and I’ll send you the agent.

If an agent can automate Salesforce reliably… it can automate anything. It's the final boss of browser agents - nested iframes, dynamic components… pure chaos. So I stopped fighting the UI. It feels like pure magic. Record the workflow once → the agent reverse-engineers the API → you get a clean, reusable API. Agents won’t use UIs. They’ll use tools they create themselves. Comment a site like “salesforce?” and I’ll send you the agent.

Magnus Müller

24,892 次观看 • 7 个月前

tired of AI agents that "10x your productivity." made something fun with openclaw. has its own personality, and does everything those "serious" agents do.

tired of AI agents that "10x your productivity." made something fun with openclaw. has its own personality, and does everything those "serious" agents do.

Leon.M

141,717 次观看 • 4 个月前

Build with AI that adapts to your workflow. Cosine for VS Code puts our agent right in your editor. Manage hundreds of agents in parallel to build and ship without limits.

Build with AI that adapts to your workflow. Cosine for VS Code puts our agent right in your editor. Manage hundreds of agents in parallel to build and ship without limits.

Cosine

172,828 次观看 • 8 个月前

Made an interactive shader to visualize our models of space-time curvature in 3D, as a lattice. Similar visualizations are typically 2D grids, and I wanted something more complete/robust/accurate.

Made an interactive shader to visualize our models of space-time curvature in 3D, as a lattice. Similar visualizations are typically 2D grids, and I wanted something more complete/robust/accurate.

Mirza Beig

103,602 次观看 • 6 个月前

🏆 Introducing TARS 1/ Your AI Executive Assistant that Turns Natural Language into Action. -> With TARS, you can seamlessly orchestrate multiple AI agents to gather insights, automate tasks, and take actions across platforms — all in one place. -> Build upon the 1st productized multi-agent orchestration (MAO) ecosystem designed for AI Agentic workflow. 🏠 Explore more:

🏆 Introducing TARS 1/ Your AI Executive Assistant that Turns Natural Language into Action. -> With TARS, you can seamlessly orchestrate multiple AI agents to gather insights, automate tasks, and take actions across platforms — all in one place. -> Build upon the 1st productized multi-agent orchestration (MAO) ecosystem designed for AI Agentic workflow. 🏠 Explore more:

Questflow

85,907 次观看 • 1 年前

New agentic short course! Multi AI Agent Systems with crewAI, built with CrewAI's founder and CEO João Moura. In this course, you'll learn how to break down complex tasks into subtasks for multiple AI agents, each playing a specialized role, to execute. For example, to generate a research report, you might have researcher, writer, and quality assurance agents collaborate. You'll define the roles, expectations, and interactions between the agents—like a manager organizing a team. You'll work with key agentic AI techniques like role-playing, tool use, memory, guardrails, and cross-agent collaboration. And you'll build your own multi-agent systems that can tackle complex tasks. I think you'll find it both productive and fun to design agents and watch them collaborate to get things done. Let me know what you think! I believe multi-agent architectures will drive significant progress in AI systems. Please sign up here!

New agentic short course! Multi AI Agent Systems with crewAI, built with CrewAI's founder and CEO João Moura. In this course, you'll learn how to break down complex tasks into subtasks for multiple AI agents, each playing a specialized role, to execute. For example, to generate a research report, you might have researcher, writer, and quality assurance agents collaborate. You'll define the roles, expectations, and interactions between the agents—like a manager organizing a team. You'll work with key agentic AI techniques like role-playing, tool use, memory, guardrails, and cross-agent collaboration. And you'll build your own multi-agent systems that can tackle complex tasks. I think you'll find it both productive and fun to design agents and watch them collaborate to get things done. Let me know what you think! I believe multi-agent architectures will drive significant progress in AI systems. Please sign up here!

Andrew Ng

349,977 次观看 • 2 年前

Custom UIs in Shortcuts! Yay or nay? 👀 I’ve wanted to build UIs in Shortcuts for a while and with the new interactive snippets, it feels more relevant than ever. So I finally prototyped an app to do it 😃 Here’s a demo shortcut that shows pollen levels in a snippet. #WWDC25

Custom UIs in Shortcuts! Yay or nay? 👀 I’ve wanted to build UIs in Shortcuts for a while and with the new interactive snippets, it feels more relevant than ever. So I finally prototyped an app to do it 😃 Here’s a demo shortcut that shows pollen levels in a snippet. #WWDC25

Simon B. Støvring

19,679 次观看 • 1 年前

Boris Cherny (Claude Code creator): "I don't prompt Claude anymore... my job is to write loops." In his latest interview, he breaks down the setup step by step. He runs /loops + a dynamic workflow + a couple hundred agents that read his GitHub, Slack, and Twitter and decide what to build next. His only job now is writing the loops that orchestrate them. That's a multi-agent workflow. I broke down how to build your own below ↓

Boris Cherny (Claude Code creator): "I don't prompt Claude anymore... my job is to write loops." In his latest interview, he breaks down the setup step by step. He runs /loops + a dynamic workflow + a couple hundred agents that read his GitHub, Slack, and Twitter and decide what to build next. His only job now is writing the loops that orchestrate them. That's a multi-agent workflow. I broke down how to build your own below ↓

Avid

26,751 次观看 • 25 天前

WELCOME TO THE WORLD OF SOVEREIGN AGENTS AN AI AGENT THAT CREATES, VERIFIES, OPENS ITS OWN ACCOUNTS, EARNS REVENUE AND PAYS FOR ITS OWN COMPUTE

WELCOME TO THE WORLD OF SOVEREIGN AGENTS AN AI AGENT THAT CREATES, VERIFIES, OPENS ITS OWN ACCOUNTS, EARNS REVENUE AND PAYS FOR ITS OWN COMPUTE

EigenCloud

13,568 次观看 • 3 个月前

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,261 次观看 • 1 年前

Grok 4.20 agents are fully customizable. Simply swipe right to “Customize Grok” and tap on the agent you want to customize. You can change the name, set custom behavior, and even add more agents. Make each agent fit your workflow and preferences.

Grok 4.20 agents are fully customizable. Simply swipe right to “Customize Grok” and tap on the agent you want to customize. You can change the name, set custom behavior, and even add more agents. Make each agent fit your workflow and preferences.

DogeDesigner

48,858 次观看 • 2 个月前

Simplest way to create an AI agent today: You don't need to write any code. You don't need to build a workflow. You can literally build agents that complete useful tasks for you using a single prompt. Check the quick video I recorded!

Simplest way to create an AI agent today: You don't need to write any code. You don't need to build a workflow. You can literally build agents that complete useful tasks for you using a single prompt. Check the quick video I recorded!

Santiago

62,639 次观看 • 8 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.

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

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.

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 次观看 • 1 年前

🚨Most GTM “AI tools” are just toys. Apollo.io just launched something different 👇 An AI Assistant that actually runs your entire go-to-market workflow.

🚨Most GTM “AI tools” are just toys. Apollo.io just launched something different 👇 An AI Assistant that actually runs your entire go-to-market workflow.

Darshal Jaitwar

58,600 次观看 • 5 个月前