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Quick breakdown of how this sequence was created using WAN 2.2 Animate agent and Multi-Angle Fashion Shoot agent One changes your appearance and location, the other generates camera movements and transitions. Short tutorial on blending both techniques Links to these agents below 👇

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GLIF

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64,815 görüntüleme • 6 ay önce •via X (Twitter)

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Tacos anyone? 🌮😋 This video was created using two agents: Motion control 🕺 Lets you add your own movement and guide how the scene animates Multi-angle photo shoot 📸 Used to generate forced-perspective-style angles that can be animated into each other Agents + tutorial below 👇
0:42

Tacos anyone? 🌮😋 This video was created using two agents: Motion control 🕺 Lets you add your own movement and guide how the scene animates Multi-angle photo shoot 📸 Used to generate forced-perspective-style angles that can be animated into each other Agents + tutorial below 👇

GLIF

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🔥 🤖 🕵️‍♂️ INTRODUCING: Meta Agent 💥 this is by far the most exciting thing I've created using AI!!! >>> made using Manus and @windsurf 🔑 Meta Agent is an AI agent that uses the OpenAI Agents SDK to GENERATE NEW AGENTS you simply tell Meta Agent in natural language the agent you want... 🤯 and Meta Agent generates it for you fully open --> link to GitHub and example walkthrough below ⬇️
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🔥 🤖 🕵️‍♂️ INTRODUCING: Meta Agent 💥 this is by far the most exciting thing I've created using AI!!! >>> made using Manus and @windsurf 🔑 Meta Agent is an AI agent that uses the OpenAI Agents SDK to GENERATE NEW AGENTS you simply tell Meta Agent in natural language the agent you want... 🤯 and Meta Agent generates it for you fully open --> link to GitHub and example walkthrough below ⬇️

Dan McAteer

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Breakfast anyone? 🍳 This is where combining tools really shines. Wan 2.2 Animate + Nano Banana + Kling 2.5 lets you bridge shots with smooth transitions, bold camera moves, and real narrative continuity. 🧵 Tutorial in the thread below:
0:39

Breakfast anyone? 🍳 This is where combining tools really shines. Wan 2.2 Animate + Nano Banana + Kling 2.5 lets you bridge shots with smooth transitions, bold camera moves, and real narrative continuity. 🧵 Tutorial in the thread below:

GLIF

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HOW AI AGENTS ACTUALLY WORK. 20 minutes. clearer than any course you've paid for. Bookmark this. watch it tonight. full breakdown of both Claude Agent Teams and Kimi Agent Swarm below.
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HOW AI AGENTS ACTUALLY WORK. 20 minutes. clearer than any course you've paid for. Bookmark this. watch it tonight. full breakdown of both Claude Agent Teams and Kimi Agent Swarm below.

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Run your PettBro Agent 24/7 and earn rewards automatically. This quick tutorial shows you how 👇
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Run your PettBro Agent 24/7 and earn rewards automatically. This quick tutorial shows you how 👇

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Next on ACP dev onboarding - in this walkthrough, John shows us how to test agents using the ACP SDK and Butler sandbox mode. This video covers: • Using our ACP SDK examples to test your agent • Testing your agent using Butler sandbox mode • How to get your agent graduated (and available for query via butler!) Useful links • ACP Node SDK: • ACP Python SDK:
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Next on ACP dev onboarding - in this walkthrough, John shows us how to test agents using the ACP SDK and Butler sandbox mode. This video covers: • Using our ACP SDK examples to test your agent • Testing your agent using Butler sandbox mode • How to get your agent graduated (and available for query via butler!) Useful links • ACP Node SDK: • ACP Python SDK:

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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:
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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 görüntüleme • 11 ay önce

As promised, here's a tutorial on how to do these special FX insane transitions on your own videos using a Glif agent! i literally use this on my iPhone on the couch, so the demo is done like that as well Link to the agent below, tag me if you're making sth cool with it!
3:25

As promised, here's a tutorial on how to do these special FX insane transitions on your own videos using a Glif agent! i literally use this on my iPhone on the couch, so the demo is done like that as well Link to the agent below, tag me if you're making sth cool with it!

fabian

11,693 görüntüleme • 8 ay önce

🤯 Hermes agent just got a Kanban task board, and it changes everything. Watch multiple AI agents collaborate in real time, each with a defined role, completing tasks with way more depth than your typical sub-agents. This is the future of multi-agent workflows 👇
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🤯 Hermes agent just got a Kanban task board, and it changes everything. Watch multiple AI agents collaborate in real time, each with a defined role, completing tasks with way more depth than your typical sub-agents. This is the future of multi-agent workflows 👇

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Put Your OpenClaw Agents To Work in the NEAR AI Agent Market! This tutorial walks you through how to set up your bot and start completing jobs all from your phone 👇

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Your agent can recreate your top-performing ads. At scale. Connect Ad Reference via MCP. The agent reads any video that worked and generates new ones built around the same patterns. Built for pipelines on OpenClaw and other agents.
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Your agent can recreate your top-performing ads. At scale. Connect Ad Reference via MCP. The agent reads any video that worked and generates new ones built around the same patterns. Built for pipelines on OpenClaw and other agents.

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Big release here! AG-UI 🤝 Google A2A Embed A2A multi-agent meshes in your frontend, and build fullstack multi-agent apps with A2A and AG-UI. 🔍How it works: Simply drop-in A2A agent endpoints, and an A2A AG-UI orchestrator agent will bi-directionally stream events between your Agents & application. Includes: - UI for A2A Interactions - Generative UI for Agent Tool Calls - Human-in-the Loop Approvals - State Synchronization (agent mesh application state) - Frontend Tool Calls for A2A Agents Watch the demo below > LangChain LangGraph & Google ADK agents working together simultaneously inside an app Demo GitHub, docs, and more 👇

CopilotKit🪁

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I built a real estate AI Agent team with multi-agents using gpt-OSS and Firecrawl. It has 3 AI agents working together as a team: 1. Property Search Agent 2. Market Analysis Agent 3. Property Valuation Agent 100% Opensource with step-by-step tutorial.
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I built a real estate AI Agent team with multi-agents using gpt-OSS and Firecrawl. It has 3 AI agents working together as a team: 1. Property Search Agent 2. Market Analysis Agent 3. Property Valuation Agent 100% Opensource with step-by-step tutorial.

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I built a multimodal AI Coding Agent team with multi-agents. It has 3 AI agents working together as a team to generate and execute the code: 1. Coding Agent using o-3 mini 2. Vision Agent using Gemini 3. Code Execution Agent using o-3 mini and E2B 100% Opensource Code.
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I built a multimodal AI Coding Agent team with multi-agents. It has 3 AI agents working together as a team to generate and execute the code: 1. Coding Agent using o-3 mini 2. Vision Agent using Gemini 3. Code Execution Agent using o-3 mini and E2B 100% Opensource Code.

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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.
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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.

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🦶🏻 I GET A KICK OUTTA YOU 🦶🏻 Looking to expand your horizons and go live elsewhere other than Twitch and YouTube? Today we have a tutorial on how to go live on Kick using Aitum Multi! 👇 Check out the video below 👇
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🦶🏻 I GET A KICK OUTTA YOU 🦶🏻 Looking to expand your horizons and go live elsewhere other than Twitch and YouTube? Today we have a tutorial on how to go live on Kick using Aitum Multi! 👇 Check out the video below 👇

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