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If you run an independent store, here's a question worth asking — how many orders are you losing every single day? In Episode 2 of our series (2/3), we show you how to build and deploy an AI customer support Agent for cross-border e-commerce with EdgeOne Makers. 💡 What...

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Tencent EdgeOne

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Everyone else is making money with AI — are you still just using it to get things done faster? In the first episode of our three-part series(1/3), we walk through EdgeOne Makers and how AI Agents are evolving from productivity tools into real products that generate revenue. 💡 What you'll see: • The next wave of AI — products, not just productivity • Two paths to monetization: existing business + Agent, or idea → MVP • One-click deployment, hosting, and global delivery with EdgeOne Makers Check the comments for event perks — join now and get up to 50M Tokens!
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Everyone else is making money with AI — are you still just using it to get things done faster? In the first episode of our three-part series(1/3), we walk through EdgeOne Makers and how AI Agents are evolving from productivity tools into real products that generate revenue. 💡 What you'll see: • The next wave of AI — products, not just productivity • Two paths to monetization: existing business + Agent, or idea → MVP • One-click deployment, hosting, and global delivery with EdgeOne Makers Check the comments for event perks — join now and get up to 50M Tokens!

Tencent EdgeOne

1,641,569 просмотров • 2 месяцев назад

You've turned your ideas and expertise into an Agent—but without DevOps skills or servers, how do you turn it into a business? In Episode 3 (3/3), we show you how to turn an idea into a validated MVP fast with EdgeOne Makers! 💡 Here's what's inside: • Turn a niche idea into a specialized AI Agent • Launch instantly with ready-made templates
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You've turned your ideas and expertise into an Agent—but without DevOps skills or servers, how do you turn it into a business? In Episode 3 (3/3), we show you how to turn an idea into a validated MVP fast with EdgeOne Makers! 💡 Here's what's inside: • Turn a niche idea into a specialized AI Agent • Launch instantly with ready-made templates

Tencent EdgeOne

1,561,186 просмотров • 2 месяцев назад

Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.
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Here is how simple it is to build a UI front-end for an AI agent (assuming you are using . The video here is 90 seconds and will show you everything you need to connect an agent to a web app: 1. Set up CopilotKit🪁 in your app 1. Copy the agent's localhost URL from LangGraph Studio 2. Paste that URL into a CopilotKit🪁 remote endpoint That's all you need to get a front-end to interact with the agent! The secret sauce here is CoAgents, an open-source library. You can use CoAgents to integrate any agent with your web application. Here is what you get: • Human-in-the-loop to steer and correct the agent • Stream intermediate agent state • Real-time state sharing between the agent and the application • Agentic generative UI to build trust that the agent is on the right path Watch the attached demo so you see it in action.

Santiago

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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.
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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

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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.

Johnny

27,179 просмотров • 1 год назад

You’ve heard about AgentKit and want to build an economically capable agent that can start earning for you. But where do you start if you don't already have an agent? Start with 🦞 ClawUp simplifies the agent-building process so you can deploy an agent without handling the full setup manually. The basic process: 1. Create your agent in ClawUp 2. Define its role, behavior, and tools 3. Deploy it to your preferred channel 4. Add AgentKit when you want economic capabilities 5. Enable wallets, payments, identity, reputation, and onchain actions ClawUp gets the agent running. AgentKit gives it the ability to transact and much more. Together, they give developers a practical path from idea → deployed agent → economically capable agent. Demo below 👇
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You’ve heard about AgentKit and want to build an economically capable agent that can start earning for you. But where do you start if you don't already have an agent? Start with 🦞 ClawUp simplifies the agent-building process so you can deploy an agent without handling the full setup manually. The basic process: 1. Create your agent in ClawUp 2. Define its role, behavior, and tools 3. Deploy it to your preferred channel 4. Add AgentKit when you want economic capabilities 5. Enable wallets, payments, identity, reputation, and onchain actions ClawUp gets the agent running. AgentKit gives it the ability to transact and much more. Together, they give developers a practical path from idea → deployed agent → economically capable agent. Demo below 👇

GOAT Network

74,749 просмотров • 4 месяцев назад

Now to onboard more builders. We've put together a short dev onboarding video walking through: - Part 1: How to set up your provider agent config on - Part 2: How to set up a requestor agent config to run tests with the provider agent Next time we'll show you how to get started with testing these agent using our SDK examples! If you're exploring monetising your agent for agent-to-agent or consumer-to-agent commerce, start here. Part 1:
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Now to onboard more builders. We've put together a short dev onboarding video walking through: - Part 1: How to set up your provider agent config on - Part 2: How to set up a requestor agent config to run tests with the provider agent Next time we'll show you how to get started with testing these agent using our SDK examples! If you're exploring monetising your agent for agent-to-agent or consumer-to-agent commerce, start here. Part 1:

Celeste Ang

34,311 просмотров • 8 месяцев назад

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.
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Matt Schlicht

290,870 просмотров • 10 месяцев назад

Now you can use your favorite AI agent to control your Coinbase account (or a sub-account), with Coinbase for Agents. Here’s a quick demo on how to set it up and some of the cool things you can get your agent to do.
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Now you can use your favorite AI agent to control your Coinbase account (or a sub-account), with Coinbase for Agents. Here’s a quick demo on how to set it up and some of the cool things you can get your agent to do.

Brian Armstrong

213,812 просмотров • 3 месяцев назад

Imagine a computer where you don’t need to learn 10 apps to get work done. You just tell it what you want, and it adapts to how you work. I tested Happycapy with a real use case and created an image and a video. No coding, no complex software. Do this: - Build automations that run on schedule - Deploy agent teams that work for you AI molds how you work, not the other way around. If you can use a computer, you can make anything happen. Start your first Automation and Agent teams today.
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Imagine a computer where you don’t need to learn 10 apps to get work done. You just tell it what you want, and it adapts to how you work. I tested Happycapy with a real use case and created an image and a video. No coding, no complex software. Do this: - Build automations that run on schedule - Deploy agent teams that work for you AI molds how you work, not the other way around. If you can use a computer, you can make anything happen. Start your first Automation and Agent teams today.

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Is your job actually safe from AI? I’ve been thinking about this a lot. To get some real answers, I'm using Frank AI Researcher to let you talk to an AI agent yourself. It takes 5 minutes. You tell the agent what you do every day and what tech you use. Then, it gives you a "future-proof score" to show how much of your work can be automated right now. I really want to see what you guys find out. Link to talk to the agent:👇
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Is your job actually safe from AI? I’ve been thinking about this a lot. To get some real answers, I'm using Frank AI Researcher to let you talk to an AI agent yourself. It takes 5 minutes. You tell the agent what you do every day and what tech you use. Then, it gives you a "future-proof score" to show how much of your work can be automated right now. I really want to see what you guys find out. Link to talk to the agent:👇

AI Panda

70,835 просмотров • 5 месяцев назад

New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!
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New short course: Serverless Agentic Workflows with Amazon Bedrock. Learn to build and deploy serverless agents in this course created with Amazon Web Services and taught by Mike G Chambers, a Senior Developer Advocate at AWS specializing in GenAI. (Disclosure: I serve on Amazon's board.) Generative AI applications are becoming more complex, sophisticated, and agentic. Agentic applications have workloads that can be hard to predict in advance -- for example, what tools will it decide to call? -- and a serverless architecture helps you efficiently providing on-demand resources. This course teaches you to build and deploy a serverless agentic application. You’ll learn to create agents with tools, code execution, and guardrails, and build responsible agents for business use cases: - Build a customer service bot for a fictional tea mug business that can answering questions, retrieve information, and process orders. - Connect your customer service agent to a CRM to get customer info and log support tickets in real-time. - Explore how you invoke the agent, and see the trace to review the agent’s thought process and observation loop until it reaches its final output. - Attach a code interpreter to your agent, giving it the ability to perform accurate calculations by writing and running its own Python code. - Implement guardrails to prevent your agent from revealing sensitive information or using inappropriate language. By the end, you will have built a sophisticated AI agent capable of handling real-world customer support scenarios. Please sign up here!

Andrew Ng

81,048 просмотров • 1 год назад

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.
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🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

MIKE

39,041 просмотров • 2 месяцев назад

✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️
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✨New LangChain Academy Course: Learn to build with LangSmith Agent Builder 🪄 Learn how to build your own agents with LangSmith Agent Builder. Anyone can now build agents for complex daily tasks, without writing code. We built Agent Builder for anyone whose day gets swallowed by routine work. The research, follow-ups, updates, scheduling, and status checks that are essential to your operations, but quickly take over your calendar. Agent Builder is different from traditional workflow automations. You don’t need to map every step, tinker with if-this-then-that branching, or babysit dependencies. You just give it feedback like you would a teammate, and the agent learns using its memory. In this quickstart course, you'll learn how to: - Build an email agent - Understand what agents can do - Improve your agent - Set up triggers and your Agent Inbox Enroll for free ➡️

LangChain

26,513 просмотров • 8 месяцев назад

Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.
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Today, Sierra is releasing Ghostwriter, our agent for building agents. With Ghostwriter, you can create an AI agent for your customer experience — one that can chat, pick up the phone, speak dozens of languages, take action on your systems of record, and be protected with industry-leading guardrails — simply by having a conversation. No clicking, no forms, no menus. Codex and Claude Code have transformed how we build software, making it possible for software engineers to orchestrate and review the work rather than doing all the work themselves. We think the same transformation will happen for all software. Rather than every enterprise app having a web app for humans and an API for automation, every software platform’s UI will be an agent that can do the work on your behalf. I recorded a demo of my building and optimizing an agent with Ghostwriter so you can see how powerful and easy it is to use. It’s completely changed the way our early adopters build agents, and it’s changed the way I think about the software industry. Let me know what you think, and, if you’re interested in trying it out at your business, please reach out directly.

Bret Taylor

1,064,016 просмотров • 6 месяцев назад

New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:
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New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:

Andrew Ng

96,370 просмотров • 3 месяцев назад

Most AI support bots aren't actually solving problems. They're assigning homework. Customer: "I need an invoice." AI: "Go to Billing → Settings → Invoices." Customer: 😑 That's not resolution. That's directions. The new shift happening in AI support isn't better answers. It's agents that can actually finish the job. Instead of telling customers what to do, they can: • retrieve invoices • process refunds • cancel subscriptions • book meetings • capture leads • run approved workflows • look up live context from your systems The challenge isn't capability. It's control. Giving an AI agent access to customer systems without guardrails is a nightmare. That's why I built AI Actions and Skill Builder for DocsBot. Your agent only gets the tools, permissions, and workflows you explicitly approve, scoped to the customer it's helping. The goal isn't smarter chatbots. The goal is fewer unresolved tickets. What's the first support task you'd trust an AI agent to complete end-to-end?
1:52

Most AI support bots aren't actually solving problems. They're assigning homework. Customer: "I need an invoice." AI: "Go to Billing → Settings → Invoices." Customer: 😑 That's not resolution. That's directions. The new shift happening in AI support isn't better answers. It's agents that can actually finish the job. Instead of telling customers what to do, they can: • retrieve invoices • process refunds • cancel subscriptions • book meetings • capture leads • run approved workflows • look up live context from your systems The challenge isn't capability. It's control. Giving an AI agent access to customer systems without guardrails is a nightmare. That's why I built AI Actions and Skill Builder for DocsBot. Your agent only gets the tools, permissions, and workflows you explicitly approve, scoped to the customer it's helping. The goal isn't smarter chatbots. The goal is fewer unresolved tickets. What's the first support task you'd trust an AI agent to complete end-to-end?

Aaron Edwards

396,250 просмотров • 3 месяцев назад