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In this simple example, we show that Claude Code can read the iMessage database on the latest version of macOS, even with a leading EDR running on the system, illustrating the impact of an adversary who can remotely control the agent. We do this using Terminator, an internal research... show more

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18,004 次观看 • 8 个月前 •via X (Twitter)

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Boris Cherny, creator of Claude Code: "We stopped fixing Claude's mistakes. We made Claude fix them itself." So while you're explaining the same bug to Claude for the third time this week, the guy who built it has an agent that never repeats a mistake. Watch him explain it, then save the full setup below 👇

Boris Cherny, creator of Claude Code: "We stopped fixing Claude's mistakes. We made Claude fix them itself." So while you're explaining the same bug to Claude for the third time this week, the guy who built it has an agent that never repeats a mistake. Watch him explain it, then save the full setup below 👇

darkzodchi

116,493 次观看 • 2 个月前

Claude Code is the best coding agent on the market, but there is a catch: you have to keep your terminal open. This is why we built Terragon: use Claude Code as a background agent.

Claude Code is the best coding agent on the market, but there is a catch: you have to keep your terminal open. This is why we built Terragon: use Claude Code as a background agent.

Sawyer Hood

150,993 次观看 • 1 年前

We just released FastA2A! 🎉 On the video, you can see on how to turn a Pydantic AI agent into an A2A server with a single line of code! You can also see how to turn an agent into a CLI chat application. 😁 Check it out on the latest PydanticAI version!

We just released FastA2A! 🎉 On the video, you can see on how to turn a Pydantic AI agent into an A2A server with a single line of code! You can also see how to turn an agent into a CLI chat application. 😁 Check it out on the latest PydanticAI version!

Pydantic

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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.

Santiago

18,715 次观看 • 1 个月前

Excited to share the multiplayer features we built to make running computer use agents easy. Here's a quick video of Claude ordering pizza and setting up Claude Code on the same computer.

Excited to share the multiplayer features we built to make running computer use agents easy. Here's a quick video of Claude ordering pizza and setting up Claude Code on the same computer.

Spencer Kinney

14,327 次观看 • 3 个月前

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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

27,176 次观看 • 1 年前

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

I cant believe this guy just made a permanent solution to context bloat and open sourced it all! when we tested this tool (Context+) for solving an issue on the OpenCode repository, the agent using this tool used ~6.5k fewer tokens, found the code and fixed it in half the time! the results were surprising: 6 to 10k tokens saved per prompt, completed task in ~2 minutes while the agent running without the tool took ~4 mins for the same and got stuck in loops bro built an entire beast by using all the modern tools that we could think of: undo trees, semantic search by meaning (by haskellforall), advanced refactoring, blast radius, advanced file context trees, restore points... i can keep going on semantic code search and context trees are the future of agentic coding and this tool proves it the feature i loved the most is semantic search and how it gets things done 2x faster with least possible tokens it makes an agent that actually knows what it’s doing and not just guessing, it makes meaning from your code similar to RAG. if you aren't optimizing your context, you are just burning money the developer says this tool is still under development, it can have unexpected behavior and the docs need updates but the video shows the reality of how fast it can be github: get here:

forloop

226,054 次观看 • 5 个月前

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AK

24,298 次观看 • 1 年前

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Santiago

72,306 次观看 • 2 年前

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Jerry Liu

48,375 次观看 • 7 个月前

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Anicet

35,735 次观看 • 7 个月前

Today's Hermes Agent Masterclass is the finale! Module 10 covers security, an important topic for running agents to ensure each agent can perform its tasks while minimizing exposure. Hermes has a ton of built-in security features. In this clip, I show how you can set approvals for each profile depending on your needs.

tonbi

382,733 次观看 • 1 个月前

Open AI released Operator, an agent that can use the browser to perform and automate tasks for you! I have built an Open Source version of Operator using Browser Use, running locally on your computer. 100% Open Source

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Sumanth

62,485 次观看 • 1 年前

AI agents can read any file the user has access to. That is a much larger surface than most security teams realize. Classification-based access policies in Box now give admins read access control for AI agents. Restrict which agents can read which content based on Box Shield classifications. Enforced automatically across every agent, regardless of which AI tool is making the request. This demo shows it in action.

AI agents can read any file the user has access to. That is a much larger surface than most security teams realize. Classification-based access policies in Box now give admins read access control for AI agents. Restrict which agents can read which content based on Box Shield classifications. Enforced automatically across every agent, regardless of which AI tool is making the request. This demo shows it in action.

Box

105,534 次观看 • 12 天前

Here is a demo of the most comprehensive research agent for your code docs, powered by Nozomio Labs. It turns your indexed repos and docs into a dynamic tree that the agent can access on the fly, using SOTA tools to reduce code hallucinations. Now using the latest Anthropic model, Claude Opus 4.5.

Here is a demo of the most comprehensive research agent for your code docs, powered by Nozomio Labs. It turns your indexed repos and docs into a dynamic tree that the agent can access on the fly, using SOTA tools to reduce code hallucinations. Now using the latest Anthropic model, Claude Opus 4.5.

Arlan

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We will be releasing an AGW CLI tool soon that allows your agents to easily interact with Abstract apps. In this demo below, you can see the end to end flow of Claude Code upvoting the top app on Abstract autonomously.

cygaar

19,224 次观看 • 4 个月前

Sam is absolutely right. The moment AI agents get full access to a computer and the web, we cross a threshold from “tools we use” to “systems that act.” This is not just another upgrade. It is the beginning of autonomous productivity at scale. Research, execution, iteration, all happening in parallel while we focus on higher level thinking. The interface era is ending. The agent era is beginning.

Sam is absolutely right. The moment AI agents get full access to a computer and the web, we cross a threshold from “tools we use” to “systems that act.” This is not just another upgrade. It is the beginning of autonomous productivity at scale. Research, execution, iteration, all happening in parallel while we focus on higher level thinking. The interface era is ending. The agent era is beginning.

VraserX e/acc

11,102 次观看 • 6 个月前

I've been using Claude Code for non-coding tasks, like sorting emails and analyzing my spending This was annoying to setup because Claude doesn’t have the right context - it can’t see my email or my credit card statements So we built a virtual filesystem that turns all of my data sources (gmail, notion, gdrive and more) into local folders on my computer I can just describe what I need (e.g. "invoices from the last week") and a folder appears on my computer with exactly those files This gives Claude context, but it also gives it memory - since it has a local filesystem that syncs in the background, it continuously gets access to my data The more things you expose as files, the more Claude can do for you

I've been using Claude Code for non-coding tasks, like sorting emails and analyzing my spending This was annoying to setup because Claude doesn’t have the right context - it can’t see my email or my credit card statements So we built a virtual filesystem that turns all of my data sources (gmail, notion, gdrive and more) into local folders on my computer I can just describe what I need (e.g. "invoices from the last week") and a folder appears on my computer with exactly those files This gives Claude context, but it also gives it memory - since it has a local filesystem that syncs in the background, it continuously gets access to my data The more things you expose as files, the more Claude can do for you

Eli Mernit

67,006 次观看 • 6 个月前

We just open-sourced Simulang, a JavaScript library that gives you and your coding agents the ability to fully control computers. Simulang is our scripting framework for desktop automation. It allows you to write deterministic computer use code that can be replayed dozens if not hundreds of times. Much faster and cheaper, compared to LLM agents. It ships with a skill out of the box. That means you can turn natural language prompts into Simulang code directly, and your agent can now see the screen, click, type, and navigate. It gives your AI agents eyes and hands to control the computer like humans do. Try these things with Simulang: - upload your pile of invoices to the expense platform - find 50 people with specific criteria on LinkedIn - open your calculator app and do some math - find all buttons on your favorite app using accessibility tree - or draw a bunny with MS paint 🐰 In this demo, we show how Simulang took over when the coding agent couldn’t open and click on the target LinkedIn profile page. Give it a try:

Simular

14,421 次观看 • 2 个月前