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Why have one AI agent handle everything when you can build a team? 🤝 Multi-agent architecture allows a main agent to spin up specialized sub-agents and handle complex tasks in parallel - making workflows faster and more efficient inside Google AI Studio. Check out the full I/O session: 🧵👇

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12,450 görüntüleme • 2 ay önce •via X (Twitter)

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It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!
1:46

It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!

elvis

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It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:
0:38

It is now way easier to build multi-agent workflows in n8n with the new AI Agent Tool node. Instead of juggling sub workflows a parent AI Agent can now use other Agents as tools even several layers deep. Max shows how a cheap GPT 4.1 nano Agent handles heavy data and sends summaries to a parent Agent saving token costs and making debugging simpler. Watch the full walkthrough:

n8n.io

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Anthropic's multi-agent researcher just explained how to actually build a graph of Claude agents: "Multi-agent is where fundamentally you have multiple agents or multiple Claudes working at the same time - one parent agent delegates tasks to five sub-agents that can each then work in parallel." the real architecture: parent agent → delegates to sub-agents (as tools) → sub-agents run in parallel → results roll back up the failure mode nobody talks about: "Overbuilt multi-agent systems spend too much time just talking back and forth with each other and not actually making progress on the main task." sound familiar? that's every bloated human org chart too in this 19-minute conversation, an Anthropic researcher lays out the real framework: parent → sub-agents → tools → context protection = the actual shape of a working agent graph
18:57

Anthropic's multi-agent researcher just explained how to actually build a graph of Claude agents: "Multi-agent is where fundamentally you have multiple agents or multiple Claudes working at the same time - one parent agent delegates tasks to five sub-agents that can each then work in parallel." the real architecture: parent agent → delegates to sub-agents (as tools) → sub-agents run in parallel → results roll back up the failure mode nobody talks about: "Overbuilt multi-agent systems spend too much time just talking back and forth with each other and not actually making progress on the main task." sound familiar? that's every bloated human org chart too in this 19-minute conversation, an Anthropic researcher lays out the real framework: parent → sub-agents → tools → context protection = the actual shape of a working agent graph

rewind

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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 👇
15:04

🤯 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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Introducing Agent Workflows. A visual editor for designing conversation flows in Agents Platform. Instead of building all of your business logic in a single agent, Workflows enable you to handle more complex scenarios by routing to specialized Subagents.
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Introducing Agent Workflows. A visual editor for designing conversation flows in Agents Platform. Instead of building all of your business logic in a single agent, Workflows enable you to handle more complex scenarios by routing to specialized Subagents.

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THE FUTURE OF WORK: AI AGENT ORG CHARTS ARE HERE Companies are creating "AI heads of departments" — each managing 5–7 sub-agents to handle tasks just like a real team. Execs delegate to a chief agent, who routes tasks to department heads, who then deploy specialized sub-agents. Employees access their department's agent through a chatbot or voicebot — making AI as easy to use as Slack. Source: benjamlns on IG
1:14

THE FUTURE OF WORK: AI AGENT ORG CHARTS ARE HERE Companies are creating "AI heads of departments" — each managing 5–7 sub-agents to handle tasks just like a real team. Execs delegate to a chief agent, who routes tasks to department heads, who then deploy specialized sub-agents. Employees access their department's agent through a chatbot or voicebot — making AI as easy to use as Slack. Source: benjamlns on IG

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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!
2:39

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!

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We’ve built a new way to ship software: Agent Teams in Antigravity. Just run /teamwork-preview to spin up a dynamic team of specialized subagents. They coordinate in the background to plan, build, and verify complex engineering tasks in parallel.
1:36

We’ve built a new way to ship software: Agent Teams in Antigravity. Just run /teamwork-preview to spin up a dynamic team of specialized subagents. They coordinate in the background to plan, build, and verify complex engineering tasks in parallel.

Google Antigravity

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Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓
2:05:53

Google just released a free 2-hour course on full Graph Engineering. How to go from one prompt to 100 agents running inside one graph: 17:44 - Build your first AI agent 39:30 - Run agents with loop engineering 1:12:38 - Turn agent loops into graphs 1:34:26 - Build agents that throttle themselves 1:55:05 - Orchestrate the full multi-agent system Most people build one agent and stop there. Google is teaching the full stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow. Self-regulating agent graphs are the new one. This 2-hour watch is worth more than most paid agent engineering courses. Bookmark and watch it today Then read the full architecture below ↓

Lunar

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Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.
2:11

Today, we’re excited to announce the general availability of the Contextual AI Platform. This is the first enterprise platform designed for building specialized RAG agents to support expert knowledge work. What is a specialized RAG agent? First, a general-purpose AI agent is one designed to automate simple daily tasks like scheduling a meeting or responding to an email. On the other hand, a specialized RAG agent is one designed to augment subject-matter experts performing complex domain-specific work. The Contextual AI Platform allows you to create these agents easily and achieve SOTA accuracy right out of the box. Check out what the Contextual AI Platform can do.

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0:22

🚨 Breaking: Google just open-sourced the Agent Development Kit (ADK) a framework for building AI agents and multi-agent systems. - Build agents in under 100 lines. - Supports MCP More information and how to get started 👇 1/5

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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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1:15

🤝 AI Agents That Work Together — Collaboration Made Simple! In this demo, John explores one of Agent Forge’s most powerful features: agent-to-agent collaboration. With Agent Forge, you can create agents with different roles, connect them, and watch them collaborate to solve complex tasks. Modular, scalable, and fully automated. 🔗 Try here:

AITECH CLOUD NETWORK

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Don't waste 2 years learning to become an AI engineer in 2026. Google just gave the complete playbook on full AI agent engineering. 2 hour course. Free: • 00:00 - build your first AI agent • 45:38 - multi agent architecture • 55:30 - AI agents with MCP tools • 1:30:45 - AI agent loop engineering • 1:39:54 - AI agent graph engineering I watched it last night. Halfway through, I realized I could break into Anthropic in weeks, not years. Bookmark now. Watch it. Then build your own AI agent with the guide below.
2:11:44

Don't waste 2 years learning to become an AI engineer in 2026. Google just gave the complete playbook on full AI agent engineering. 2 hour course. Free: • 00:00 - build your first AI agent • 45:38 - multi agent architecture • 55:30 - AI agents with MCP tools • 1:30:45 - AI agent loop engineering • 1:39:54 - AI agent graph engineering I watched it last night. Halfway through, I realized I could break into Anthropic in weeks, not years. Bookmark now. Watch it. Then build your own AI agent with the guide below.

Roan

50,366 görüntüleme • 15 gün önce

Claude Cowork and Manus just got a serious challenger 🤯 LobeHub lets you hire an entire workforce of AI agents. It’s a workspace where you can build and team up with "Agent Coworkers" to handle complex, systematic work automatically. Built on open-source LobeChat (70k stars).
1:01

Claude Cowork and Manus just got a serious challenger 🤯 LobeHub lets you hire an entire workforce of AI agents. It’s a workspace where you can build and team up with "Agent Coworkers" to handle complex, systematic work automatically. Built on open-source LobeChat (70k stars).

Alvaro Cintas

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Google just released a free 2-hour course On going from one prompt to a complete multi-agent graph: 17:44 - Build your first AI agent 39:30 - Create self-improving agent loops 1:12:38 - Connect those loops into graphs 1:34:26 - Make agents regulate themselves 1:55:05 - Orchestrate the full multi-agent system Most people are still building one agent and stopping there Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow Self-regulating agent graphs are the new one This free 2-hour course is worth more than most paid agent engineering programs Bookmark and watch it today Then read the full architecture below ↓
2:02:33

Google just released a free 2-hour course On going from one prompt to a complete multi-agent graph: 17:44 - Build your first AI agent 39:30 - Create self-improving agent loops 1:12:38 - Connect those loops into graphs 1:34:26 - Make agents regulate themselves 1:55:05 - Orchestrate the full multi-agent system Most people are still building one agent and stopping there Google is teaching the entire stack: Prompt → Agents → Loops → Graphs → Multi-Agent Systems Single agents are the old workflow Self-regulating agent graphs are the new one This free 2-hour course is worth more than most paid agent engineering programs Bookmark and watch it today Then read the full architecture below ↓

rari

42,383 görüntüleme • 17 gün önce

Introducing multi-agent orchestration in Oz, with support for Claude Code, Codex and the Warp Agent. Use /orchestrate to delegate complex tasks across a team of agents, locally or in the cloud.
2:17

Introducing multi-agent orchestration in Oz, with support for Claude Code, Codex and the Warp Agent. Use /orchestrate to delegate complex tasks across a team of agents, locally or in the cloud.

Warp

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today we're launching the AI agent stack we built that rocketed us to a $3m AI agent consultancy. we're calling it AgentPress, and it allows you to build production grade AI agents in minutes. here's a video of me creating a sales Q&A agent
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today we're launching the AI agent stack we built that rocketed us to a $3m AI agent consultancy. we're calling it AgentPress, and it allows you to build production grade AI agents in minutes. here's a video of me creating a sales Q&A agent

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