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each mac is fully controlled by a single AGENT. it can operate browsers with insane efficiency and interact directly with native mac apps. under each agent there are multiple SOTA SUBAGENTS including claude code. we can literally tell dozens of agents to post content on their own accounts simultaneously....

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Derek Nee

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27,594 次观看 • 8 个月前 •via X (Twitter)

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🚨 Secure OpenClaw - Message Your Custom AI Agent From Telegram We are excited for our first release of personal agents. You can now use Abacus AI's DeepAgent to vibe code a personal agent on Telegram Create and simply message the agent! - do tasks like respond to emails - schedule meetings - use the browser to book tickets - connect to your internal systems The agent runs on a secure environment with constraints and you can pretty much customize it exactly like you want it when you are building it This is just v1 - we are going to be launching something WAY more exciting soon

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GTA Coin

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Introducing Tapkit Tapkit is a Mac app that lets your agents use your iPhone. Tell it to do anything and it can use your phone to do it. We've been iterating on Tapkit over the last few months with our earliest users and finally feel like it's ready for general use. Today it is easy to use, supports any agent, and can even use multiple iPhones at the same time. There are so many great things that we can do with this new primitive, but I didn't want to wait any longer to share it with you. Try it now:

teej

576,141 次观看 • 23 天前

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.
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This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

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18,949 次观看 • 3 个月前

Will we have one horizontal agent or tons of vertical agents in the consumer realm? “My take on the consumer space is that you will have both horizontal and vertical agents, and the horizontal agents will interact with the vertical agents. A lot of these apps have knowledge about you and can learn things about how you interact with that app better than a general horizontal agent could. It is a better experience if there is an agent that wraps those APIs and exposes a natural language face for a horizontal agent to interact with.” Harrison Chase Love to hear your thoughts Jerry Liu Flo Crivello Garry Tan
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Will we have one horizontal agent or tons of vertical agents in the consumer realm? “My take on the consumer space is that you will have both horizontal and vertical agents, and the horizontal agents will interact with the vertical agents. A lot of these apps have knowledge about you and can learn things about how you interact with that app better than a general horizontal agent could. It is a better experience if there is an agent that wraps those APIs and exposes a natural language face for a horizontal agent to interact with.” Harrison Chase Love to hear your thoughts Jerry Liu Flo Crivello Garry Tan

Harry Stebbings

17,373 次观看 • 3 天前

My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.
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My agent is now paying for its own data. No API key. No account. No credit card. Check the video I recorded. This uses the x402 open protocol built by Coinbase, along with a simple skill. This is an open protocol governed by the Linux Foundation. To complete a goal, an agent can now search for an actor on the Apify Store, pay for it, and use it without any human intervention. The way it works is pretty simple: 1. Your agent finds an Actor it wants to use 2. It sends a request 3. The Actor sends back an HTTP 402 "Payment Required" response 4. Agent authorizes payment from a wallet in USDC on Base 5. The Actor runs 6. User receives the result The model is pay-as-you-go: the agent authorizes a spending ceiling, pays only for usage, and the remaining balance is automatically settled. This brings an entire marketplace of AI tools into the agentic economy. Here is the skill you need. Add it to your agent, and it will take care of everything for you: If you want to know how this works, including what you can do with $1, read this post: Thanks to the Apify team for partnering with me on this post.

Santiago

26,981 次观看 • 3 个月前

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🚀 Introducing Queue: A Smarter Way to Build with Replit Agent Today, we’re excited to launch Queue, a powerful new capability designed to enhance your experience with Replit Agent. With Queue, you can submit multiple tasks while your Agent is still working—no more waiting around or breaking your flow. As each task completes, the Agent automatically moves to the next. You can: ✅ Add multiple tasks for the Agent to process in order. ✅ Edit, reorder, or reprioritize messages on the fly. ✅ Attach files and adjust settings—including toggling extended thinking or selecting a different model—per task.

Replit ⠕

75,751 次观看 • 1 年前

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Bash is all you need! Which is why I'm introducing my holiday project: just-bash just-bash is a pretty complete implementation of bash in TypeScript designed to be used as a bash tool by AI agents. Because it turns out agents love exploring data via shell scripts, even beyond coding. It comes with grep, sed, awk and the 99th percentile features that an agent like Claude Code or Cursor would use. In fact, Claude Code can use it for secure bash execution. In the package - A bash-tool for AI SDK - A binary for use by yourself or your coding agents - An overlay filesystem to feed files to your agent securely - A Vercel Sandbox compatible API, so you can quickly upgrade to a real VM if you need to run binaries - An example AI agent that explores the just-bash code base using just-bash - I imported the Oils shell bash compatibility suite and just-bash passes a very good chunk What is interesting about this codebase: It was essentially entirely written by Opus 4.5. Coding agents love bash and they are good at reproducing it. They are also great at text-book recursive descent parsers and AST tweet-walk interpreters. That said, it is, like, a lot of code and I didn't read it all 😅. This is very much a hack, but it also seems to be _really_ useful. I haven't really found anything agents want to use that it doesn't support and it's fast and secure (caveats apply). It doesn't have write access to your computer and the filesystem is given a root that the agent cannot escape from. Find it at Related: Our recent blog post how we migrated our data analysis agent to bash tools and achieved incredible quality improvements The video shows the example agent investigating the just-bash code base

Malte Ubl

125,326 次观看 • 9 个月前

Mac Mini is super nice because you can use native iMessage for talking with OpenClaw. The only problem is that it's very expensive and you need to always have your Mac Mini on to run this setup. So I made a plugin to allow anyone on any computer (either Linux, Windows, or Mac) to be able to have access to iMessage natively. Even better, it has access to all of the reactions, triple dot indicator, etc. Check it out and let me know what you think.
1:33

Mac Mini is super nice because you can use native iMessage for talking with OpenClaw. The only problem is that it's very expensive and you need to always have your Mac Mini on to run this setup. So I made a plugin to allow anyone on any computer (either Linux, Windows, or Mac) to be able to have access to iMessage natively. Even better, it has access to all of the reactions, triple dot indicator, etc. Check it out and let me know what you think.

Nick Vasilescu

265,938 次观看 • 8 个月前

Let me explain why I launched $KEYS. CA: 3BSoYDZsPupZ15iBzJbJJjZKLiyWEqLxexJX84rBpump is the first SocialFi experience for AI agents. It’s a project that’s very special to me that I’ve been working on daily for the last four months. Right now, everyone is building their own Agent, completely silo to their own computer or Mac mini. Transferring that information agent-to-agent in a simple, structured, and easy form is not possible right now. This is why I built I thought a lot about whether or not to launch an official token for Agent Keys and how I wanted to do it. The only way I really wanted to do it was if it can benefit the platform by increasing exposure and creating an increase in users. So I’ve decided to buy 50% of the supply to AirDrop directly to users over the next six months. Each AirDrop will happen at the end of each month, with the first AirDrop happening at the end of June. More details on how each AirDrop will work soon. Some of you may be wondering about the future of $OSHI. Oshi got us into the Bags hackathon and we won. $OSHI token will still be the home for all my AI Agents and runs as the showcase of how an agent with a token can properly integrate it into AgentKeys, a live example of the platform doing exactly what it was built to do. So welcome to Agent Keys, the first ever airdrop for AI agents. Sign up your agent today on and start collecting KeyCards today!
2:55

Let me explain why I launched $KEYS. CA: 3BSoYDZsPupZ15iBzJbJJjZKLiyWEqLxexJX84rBpump is the first SocialFi experience for AI agents. It’s a project that’s very special to me that I’ve been working on daily for the last four months. Right now, everyone is building their own Agent, completely silo to their own computer or Mac mini. Transferring that information agent-to-agent in a simple, structured, and easy form is not possible right now. This is why I built I thought a lot about whether or not to launch an official token for Agent Keys and how I wanted to do it. The only way I really wanted to do it was if it can benefit the platform by increasing exposure and creating an increase in users. So I’ve decided to buy 50% of the supply to AirDrop directly to users over the next six months. Each AirDrop will happen at the end of each month, with the first AirDrop happening at the end of June. More details on how each AirDrop will work soon. Some of you may be wondering about the future of $OSHI. Oshi got us into the Bags hackathon and we won. $OSHI token will still be the home for all my AI Agents and runs as the showcase of how an agent with a token can properly integrate it into AgentKeys, a live example of the platform doing exactly what it was built to do. So welcome to Agent Keys, the first ever airdrop for AI agents. Sign up your agent today on and start collecting KeyCards today!

fxnction

27,570 次观看 • 4 个月前

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.
1:30

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.

Max Blade

29,932 次观看 • 3 个月前

Most AI coding setups right now look something like this: one agent in a terminal, another in a browser tab, a chat window somewhere else, and you in the middle copy-pasting diffs like a very tired air traffic controller. JetBrains just launched something aimed right at that mess. It's called JetBrains Air, and it lives inside their IDEs. The short version: Air lets you direct multiple coding agents, run their tasks in parallel, and review their work without ever leaving your IDE. Here's what stood out to me: 👇 1. You pick the agents. Air isn't tied to a single agent or provider. You can use the ones you already like. That matters more than it sounds, because the "best" coding agent changes every few months, and nobody wants to rebuild their whole workflow each time. 2. Parallel work without losing track. You can run several agent sessions at once, even across different projects. Air shows you where your attention is needed, so you're not hopping between tabs to find out which agent is stuck. 3. You stay in control. You can follow what each agent is doing, give it input, inspect the changes, and review the output before accepting anything. Nothing lands in your codebase just because an agent felt confident. 4. The agents get IDE smarts too. This is the part I find most interesting. JetBrains IDEs already have great code navigation, refactoring, testing, and debugging. With Air, both you and your agents work with that context. So the agents aren't guessing blind inside a chat box, and when something needs a human, the real tools are right there. The bigger idea here is that agents become part of your development workflow instead of a separate chat you keep switching to. There's also a nice bonus. For a limited time, JetBrains is offering Junie Lite for free (fair use applies). It's their own coding agent paired with a highly efficient model. It isn't pitched as a frontier-level agent. Think of it as a solid, free baseline for trying out Air and running everyday tasks. Air works in any JetBrains IDE and is in early access right now. If you write code with agents, give it a try: #ad
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Most AI coding setups right now look something like this: one agent in a terminal, another in a browser tab, a chat window somewhere else, and you in the middle copy-pasting diffs like a very tired air traffic controller. JetBrains just launched something aimed right at that mess. It's called JetBrains Air, and it lives inside their IDEs. The short version: Air lets you direct multiple coding agents, run their tasks in parallel, and review their work without ever leaving your IDE. Here's what stood out to me: 👇 1. You pick the agents. Air isn't tied to a single agent or provider. You can use the ones you already like. That matters more than it sounds, because the "best" coding agent changes every few months, and nobody wants to rebuild their whole workflow each time. 2. Parallel work without losing track. You can run several agent sessions at once, even across different projects. Air shows you where your attention is needed, so you're not hopping between tabs to find out which agent is stuck. 3. You stay in control. You can follow what each agent is doing, give it input, inspect the changes, and review the output before accepting anything. Nothing lands in your codebase just because an agent felt confident. 4. The agents get IDE smarts too. This is the part I find most interesting. JetBrains IDEs already have great code navigation, refactoring, testing, and debugging. With Air, both you and your agents work with that context. So the agents aren't guessing blind inside a chat box, and when something needs a human, the real tools are right there. The bigger idea here is that agents become part of your development workflow instead of a separate chat you keep switching to. There's also a nice bonus. For a limited time, JetBrains is offering Junie Lite for free (fair use applies). It's their own coding agent paired with a highly efficient model. It isn't pitched as a frontier-level agent. Think of it as a solid, free baseline for trying out Air and running everyday tasks. Air works in any JetBrains IDE and is in early access right now. If you write code with agents, give it a try: #ad

Mushfiq Sajib

40,469 次观看 • 15 天前

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.
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This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,922 次观看 • 10 个月前