Загрузка видео...

Не удалось загрузить видео

На главную

Next week we're open sourcing Agent Builder - a visual n8n-style workflow builder for AI agents. Build AI agent workflows with a visual canvas by connecting , LLMs, logic nodes, and MCPs, then deploy as an API. Stay tuned for this one 👀

CalebPeffer's profile picture

Caleb Peffer (Hiring!)

6,708 subscribers

252,203 просмотров • 11 месяцев назад •via X (Twitter)

Наука и технологии
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Build AI Agents and connect them to 100,000+ APIs with Postman's AI Agent Builder. It has a drag-and-drop visual interface to build agent workflows with no code.
0:13

Build AI Agents and connect them to 100,000+ APIs with Postman's AI Agent Builder. It has a drag-and-drop visual interface to build agent workflows with no code.

Shubham Saboo

152,567 просмотров • 1 год назад

Figma canvas to build AI agent workflows. Sim is a lightweight, user-friendly platform for building AI agent workflows in minutes. It natively supports all major LLMs, Vector DBs, etc. 100% open-source with 7k+ stars!
0:16

Figma canvas to build AI agent workflows. Sim is a lightweight, user-friendly platform for building AI agent workflows in minutes. It natively supports all major LLMs, Vector DBs, etc. 100% open-source with 7k+ stars!

Avi Chawla

79,322 просмотров • 1 год назад

Drag-and-drop UI to build AI agents! Langflow is a powerful visual tool for building and deploying AI-powered agents and workflows—without writing any code. Supports all major LLMs, vector DBs, etc. 100% open-source, 62k+ stars 🌟
0:11

Drag-and-drop UI to build AI agents! Langflow is a powerful visual tool for building and deploying AI-powered agents and workflows—without writing any code. Supports all major LLMs, vector DBs, etc. 100% open-source, 62k+ stars 🌟

Akshay 🚀

208,132 просмотров • 1 год назад

Your OpenClaw agents 🦞 just unlocked a paycheck. Build agents with Warden → deploy on Warden → get paid. They’re eligible for the $1,000,000 in Agent Builder Incentives. Build agents with Warden → deploy on Warden → get paid. Agents building agents. Agents earning money. Build anywhere. Deploy on Warden.
0:14

Your OpenClaw agents 🦞 just unlocked a paycheck. Build agents with Warden → deploy on Warden → get paid. They’re eligible for the $1,000,000 in Agent Builder Incentives. Build agents with Warden → deploy on Warden → get paid. Agents building agents. Agents earning money. Build anywhere. Deploy on Warden.

Warden / Halo

207,147 просмотров • 7 месяцев назад

We're dropping Open Scouts next week - an AI web monitoring platform. Set up AI agents that monitor the web for anything you care about and get notified when they find what you're looking for. An open source example built with , AI SDK, and Resend! Stay tuned 👀
0:14

We're dropping Open Scouts next week - an AI web monitoring platform. Set up AI agents that monitor the web for anything you care about and get notified when they find what you're looking for. An open source example built with , AI SDK, and Resend! Stay tuned 👀

Eric Ciarla (hiring)

54,142 просмотров • 9 месяцев назад

📢 NEW ADOPTION ALERT 📢 We're excited to welcome GriffinAI | The #1 AI Agent Builder for DeFi 🤖 to the Vanar AI agent Ecosystem! 🎉 Griffin AI, a pioneer in decentralized networks for building and monetizing AI agents in Web3, will officially support the Vanar blockchain. Together, we’re driving the next wave of AI innovation.
0:18

📢 NEW ADOPTION ALERT 📢 We're excited to welcome GriffinAI | The #1 AI Agent Builder for DeFi 🤖 to the Vanar AI agent Ecosystem! 🎉 Griffin AI, a pioneer in decentralized networks for building and monetizing AI agents in Web3, will officially support the Vanar blockchain. Together, we’re driving the next wave of AI innovation.

Vanar

34,050 просмотров • 1 год назад

Drag & Drop to build AI agents 🤯 Introducing n8n, a visual UI for building AI agents with LangChain without writing a single line of Python code. Now build automation around LLM apps with NoCode and give superpowers to ChatGPT.
0:18

Drag & Drop to build AI agents 🤯 Introducing n8n, a visual UI for building AI agents with LangChain without writing a single line of Python code. Now build automation around LLM apps with NoCode and give superpowers to ChatGPT.

Shubham Saboo

548,853 просмотров • 2 лет назад

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.
0:14

OpenClaw, but built for normal people. Sim is an open-source platform that lets you build AI agent workflows on a drag-and-drop canvas. Connect them to channels like Telegram and WhatsApp and deploy without writing a single line of code. They also have a built-in Copilot that generates entire workflows from plain English, which you can then tweak and customize in the UI. Key features: - Free and open-source (Apache 2.0) - Vector store integration for RAG-grounded agents - Self-host with one command (`npx simstudio`) - Run fully local with Ollama, no API keys needed - Supports vLLM for production-grade self-hosted inference The thing I really like about Sim is the level of control you get. You can add conditional branching, parallel execution, human-in-the-loop approval gates, and even nest workflows inside other workflows. Everything is visible on the canvas, so you know exactly what your agent is doing at every step. And you can build a workflow in Sim, deploy it as an MCP server, and plug it into any agent, including OpenClaw. I've shared the link to Sim's GitHub repo in the next tweet.

Akshay 🚀

52,426 просмотров • 6 месяцев назад

😊what’s coming next for #Unibase? Introducing BitAgent — A Decentralized Multi-Agent Collaboration Platform, powered by $UB. Immortal AI Agents with on-chain identity, permanent memory, and cross-platform collaboration are here. 🧵 👉 Stay tuned — the first Agent is AWAKENING, sealed and verified by Unibase 👀
0:14

😊what’s coming next for #Unibase? Introducing BitAgent — A Decentralized Multi-Agent Collaboration Platform, powered by $UB. Immortal AI Agents with on-chain identity, permanent memory, and cross-platform collaboration are here. 🧵 👉 Stay tuned — the first Agent is AWAKENING, sealed and verified by Unibase 👀

Unibase

11,975 просмотров • 11 месяцев назад

✨ Advanced Visual Intelligence Agent! Nano Banana PRO is an AI-powered visual generation agent available on Agent Forge. Using supported third-party AI models and image-processing tools, it enables users to generate images from text-based prompts for creative exploration, drafts, prototypes, and visual experimentation. Whether you’re working on early design concepts, artistic ideas, or automated content workflows, Nano Banana PRO helps streamline the process by converting written prompts into visual outputs within the Agent Forge environment. 🔗
0:12

✨ Advanced Visual Intelligence Agent! Nano Banana PRO is an AI-powered visual generation agent available on Agent Forge. Using supported third-party AI models and image-processing tools, it enables users to generate images from text-based prompts for creative exploration, drafts, prototypes, and visual experimentation. Whether you’re working on early design concepts, artistic ideas, or automated content workflows, Nano Banana PRO helps streamline the process by converting written prompts into visual outputs within the Agent Forge environment. 🔗

AITECH CLOUD NETWORK

62,330 просмотров • 9 месяцев назад

Alchemist AI 3.5 is here 🪄 Try it out now ▶️ ⚙️ Entirely rebuilt with a proprietary multi-agent engine ⚡️ Faster, smarter generations with real-time logic 🧠 16+ LLMs running in parallel across 8 orchestration layers 🎮 Build 3D games & apps live as you go Experience our flagship evolution and stay tuned for what's next!
0:18

Alchemist AI 3.5 is here 🪄 Try it out now ▶️ ⚙️ Entirely rebuilt with a proprietary multi-agent engine ⚡️ Faster, smarter generations with real-time logic 🧠 16+ LLMs running in parallel across 8 orchestration layers 🎮 Build 3D games & apps live as you go Experience our flagship evolution and stay tuned for what's next!

ALCHEMIST AI 🔮

102,980 просмотров • 1 год назад

“When you connect nodes together, you're designing a workflow that moves and thinks like you do.” Learn the basics in our Intro to Fuser: A Visual Workspace for AI-Powered Creative Workflows. 🔗 ↓
0:17

“When you connect nodes together, you're designing a workflow that moves and thinks like you do.” Learn the basics in our Intro to Fuser: A Visual Workspace for AI-Powered Creative Workflows. 🔗 ↓

Fuser

21,284 просмотров • 9 месяцев назад

LayerAI AI Agent Manifesto is Live: The Path Forward 🧬 We've made it easy for ecosystem veterans & newcomers to get excited about the market & product opportunity we're tackling next: AI Agent Infrastructure. We're building an AI-powered agent platform where people can deploy, market, and succeed with this new token subcategory. At the heart of this transformation lies a challenge: primitive & so far limited tech & AI capabilities of incumbent platforms. We believe that LayerAI is equipped to rise as the new leading infrastructure provider for this market. LayerAI has already demonstrated market validation for AI Agents and looks to build on what we believe is the very start of this category in web3. 👉 Explore now:
0:19

LayerAI AI Agent Manifesto is Live: The Path Forward 🧬 We've made it easy for ecosystem veterans & newcomers to get excited about the market & product opportunity we're tackling next: AI Agent Infrastructure. We're building an AI-powered agent platform where people can deploy, market, and succeed with this new token subcategory. At the heart of this transformation lies a challenge: primitive & so far limited tech & AI capabilities of incumbent platforms. We believe that LayerAI is equipped to rise as the new leading infrastructure provider for this market. LayerAI has already demonstrated market validation for AI Agents and looks to build on what we believe is the very start of this category in web3. 👉 Explore now:

LayerAI | AI2Earn

158,959 просмотров • 1 год назад

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.
0:10

OpenAI's AgentKit will be so insane, build every step of agents on one platform. These visual agent builders make the whole process of iterating and launching agents far more efficient. It sits on top of the Responses API and unifies the tools that were previously scattered across SDKs and custom orchestration. It lets developers create agent workflows visually, connect data sources securely, and measure performance automatically without coding every layer by hand. The core of AgentKit is the Agent Builder, a drag-and-drop canvas where each node represents an action, guardrail, or decision branch. Developers can link these nodes into multi-agent workflows, preview results instantly, and version each setup. It supports inline evaluation so that developers can see how changes affect output before deploying. The Connector Registry is a single admin panel that manages how data and tools connect across the OpenAI ecosystem. It centralizes integrations like Google Drive, SharePoint, Dropbox, and Microsoft Teams. Large organizations can govern access and flow of data between agents securely under one global console. ChatKit provides a ready-to-use chat interface for embedding agents inside apps or websites. It manages streaming, message threads, and model reasoning displays automatically. Developers can skin the interface to match their product without writing custom front-end code. Under the hood, all these blocks use the same execution core that runs agent reasoning through OpenAI’s APIs. Workflows in Agent Builder compile down to structured instructions for the Responses API, which handles model calls, tool use, and context passing. Connector Registry handles authentication and routing for external tools, while Evals and RFT provide feedback loops that improve agents over time. This integration means developers no longer need to handle orchestration logic, model evaluation pipelines, or safety layers separately. Everything runs natively within OpenAI’s control plane with managed security, automatic versioning, and built-in testing. In short, AgentKit standardizes the entire life cycle of an AI agent—from visual design to deployment and performance tuning—inside a single unified system.

Rohan Paul

178,460 просмотров • 11 месяцев назад

How do you build AI agents that remember and learn from past conversations? Watch this episode of The Agent Factory for a deep dive into building agents with memory, including the fundamentals of agent memory, Vertex AI Memory Bank, and more →
0:18

How do you build AI agents that remember and learn from past conversations? Watch this episode of The Agent Factory for a deep dive into building agents with memory, including the fundamentals of agent memory, Vertex AI Memory Bank, and more →

Google Cloud Tech

12,952 просмотров • 1 год назад

Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the following topics: - Agent Skills - Agentic Image Generation - 30 Days of Hermes Agents - Prompt Engineering with Agents I am confident that with our new DAIR.AI platform, anyone can learn to become a top AI builder by building and acquiring highly-demanded AI skills. And there is a lot more landing in the coming weeks.
0:14

Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with coding agents. To start, we are launching 4 new hands-on labs on the following topics: - Agent Skills - Agentic Image Generation - 30 Days of Hermes Agents - Prompt Engineering with Agents I am confident that with our new DAIR.AI platform, anyone can learn to become a top AI builder by building and acquiring highly-demanded AI skills. And there is a lot more landing in the coming weeks.

elvis

19,058 просмотров • 3 месяцев назад

One interesting feature in Agent Builder is ChatKit and .widget support. It also refers to an application called Widget Studio where users will be able to develop UI widgets for their agents. A big differentiation point 👀
0:19

One interesting feature in Agent Builder is ChatKit and .widget support. It also refers to an application called Widget Studio where users will be able to develop UI widgets for their agents. A big differentiation point 👀

TestingCatalog News 🗞

50,084 просмотров • 11 месяцев назад

Cluster x Mind Network Every payment an AI agent makes through an open standard is public by default. Sender, receiver, token, amount, permanently onchain. Fine for a hobby agent. A non-starter for a business running agents at scale. Mind Network is fixing that with Cluster.
0:20

Cluster x Mind Network Every payment an AI agent makes through an open standard is public by default. Sender, receiver, token, amount, permanently onchain. Fine for a hobby agent. A non-starter for a business running agents at scale. Mind Network is fixing that with Cluster.

Cluster Protocol

71,430 просмотров • 2 месяцев назад