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Agent sessions work well for focused tasks, but most real projects are too broad and complex for a single context window to hold. The more an agent sees, the less reliable it becomes. We built Missions to fix this.

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Factory

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45,282 görüntüleme • 4 ay önce •via X (Twitter)

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Last, but not least, don't sleep on this one: Le Chat now has Work mode (Preview) — a powerful agent for complex long-horizon tasks like research, analysis, and actions across your connected tools. Connectors are on by default so the agent pulls context from docs, email, and calendars as it works, and sessions persist across many turns until the task is complete.
1:03

Last, but not least, don't sleep on this one: Le Chat now has Work mode (Preview) — a powerful agent for complex long-horizon tasks like research, analysis, and actions across your connected tools. Connectors are on by default so the agent pulls context from docs, email, and calendars as it works, and sessions persist across many turns until the task is complete.

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We open-sourced our agent skills ecosystem, built specifically for complex end-to-end browser tasks. Type in any domain, and researches an approach to reliably complete your task, contributing it back to the knowledge base for other agents. Watch our agent fetch Amazon listings in real-time, driven entirely by a custom browser skill:

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Agents shouldn't see your secrets. Today, most deployments hand the agent a real API key and hope for the best. That's why we're launching Infisical Agent Proxy. You give an agent a fake API key. The agent uses that key and the proxy swaps it for the real one at the network boundary before forwarding it outbound to its destination. An agent can't leak a secret it never sees. Build and deploy AI agents securely with Infisical Agent Proxy.
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Agents shouldn't see your secrets. Today, most deployments hand the agent a real API key and hope for the best. That's why we're launching Infisical Agent Proxy. You give an agent a fake API key. The agent uses that key and the proxy swaps it for the real one at the network boundary before forwarding it outbound to its destination. An agent can't leak a secret it never sees. Build and deploy AI agents securely with Infisical Agent Proxy.

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Introducing Toggle for OpenClaw🦞 For the first time ever your Agent can see everything you do on the web. This is real-time context on your work day. Toggle AI analyses all browser actions, clicks, work, meetings and documents -> into AI context of what Projects / Tasks / Tools you are working on. Check it out👇

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The paradigm shift is here: We are moving from a "Human-First" internet to an "Agent-First" internet. 🤖 In the latest episode of the AI on Air podcast, our CTO Scott Shi - e/acc dives deep into the future of the Agent-to-Agent (A2A) economy. Imagine a world where your AI assistant doesn't just search the web, but autonomously hires and pays other specialized agents to complete complex tasks for you. The infrastructure for this autonomous machine economy is being built right now. Are you ready for the future of AI payments? Watch the full episode to learn more⬇️

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We're excited to announce Autotab 1.0. The first AI agent that you onboard, not integrate. Models have the intelligence required for most work—but they’re limited by context, tools, and coherence over long tasks. We’ve built Autotab to unhobble models on these bottlenecks 🧵
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We're excited to announce Autotab 1.0. The first AI agent that you onboard, not integrate. Models have the intelligence required for most work—but they’re limited by context, tools, and coherence over long tasks. We’ve built Autotab to unhobble models on these bottlenecks 🧵

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Inviting early beta testers for our upcoming SWE agent, Asteria. We're solving AI code comprehension, where the context window and the size of your codebase are no longer limitations, and reinventing the UX of how coding agents are currently implemented. We initially built this to address false positives and enhance accuracy for our SAST agent, which autonomously identifies security vulnerabilities, traces how a payload would flow through code, and ultimately demonstrates an actual exploit. The performance improved so significantly that we decided to test it on realistic engineering tasks on large codebases and witnessed SOTA results. Reply "access" if you'd like to be an early beta tester, a lot of quirks to fix.
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Inviting early beta testers for our upcoming SWE agent, Asteria. We're solving AI code comprehension, where the context window and the size of your codebase are no longer limitations, and reinventing the UX of how coding agents are currently implemented. We initially built this to address false positives and enhance accuracy for our SAST agent, which autonomously identifies security vulnerabilities, traces how a payload would flow through code, and ultimately demonstrates an actual exploit. The performance improved so significantly that we decided to test it on realistic engineering tasks on large codebases and witnessed SOTA results. Reply "access" if you'd like to be an early beta tester, a lot of quirks to fix.

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got Claude Agent SDK working in Cloudflare Developers containers and built my own code fixer agent, check it out!👇 uses the github mcp/git cli/skills to clone the repo, understand, make the fix, and open a pr when done. planning on more agents focused on non-code tasks 👀
1:01

got Claude Agent SDK working in Cloudflare Developers containers and built my own code fixer agent, check it out!👇 uses the github mcp/git cli/skills to clone the repo, understand, make the fix, and open a pr when done. planning on more agents focused on non-code tasks 👀

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34:40

Your AI agent has your API keys. A poisoned document tells it to curl your secrets to an attacker's server. This is credential exfiltration, and it's the #1 risk in agentic AI right now. The fix is removing the secret from the agent entirely. Agent Vault sits between your agent and the APIs it calls. The agent gets dummy credentials, and Agent Vault swaps in the real ones at the network layer. The agent never sees your keys. We just dropped a full video + guide on connecting Hermes Agent to Agent Vault on a VPS!

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Turn any repetitive task into an API. We build an agent that reverse-engineers the network requests to create APIs/tools for your tasks. This is a new paradigm for browser agents, making them reliable, fast, and cheap.
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Turn any repetitive task into an API. We build an agent that reverse-engineers the network requests to create APIs/tools for your tasks. This is a new paradigm for browser agents, making them reliable, fast, and cheap.

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🚀 New LangChain Academy Course: Building Reliable Agents 🚀 Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models. Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design. The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement. You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents. Enroll for free ➡️

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I intended to build an outbound sales agent but it didn't work out due to some geographical restrictions which I'm looking for alternative ways to fix. But I went ahead to create an inbound sales Agent instead. I used to have this work.
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I intended to build an outbound sales agent but it didn't work out due to some geographical restrictions which I'm looking for alternative ways to fix. But I went ahead to create an inbound sales Agent instead. I used to have this work.

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1:01

Introducing Agent 2.0 Go from a simple prompt to fully realized marketing briefs and campaign assets right inside of Runway Agent. You can also easily analyze your performance data to improve your creative and scale it across platforms, formats and markets. Agent is being built to become the most capable autonomous agent for real-world work.

Runway

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The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.
2:15

The bottleneck in coding is now the time it takes a human to review agent-generated code. But existing review UIs don't work well for agents. So we built a new one into Amp.

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We raised $6.5M to build the agent for professionals. When your reputation is on the line, you need an agent that's reliable, secure, and one step ahead. Try it now at
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We raised $6.5M to build the agent for professionals. When your reputation is on the line, you need an agent that's reliable, secure, and one step ahead. Try it now at

Kevin Yang

74,172 görüntüleme • 5 ay önce

THIS GUY IS RUNNING A 5-AGENT OPENCLAW TEAM 24/7 FOR UNDER $50 A MONTH five agents all running continuously and handing tasks to each other > research agent tracking trends and competitors > writing agent handling marketing content and drafts > ops agent managing emails and scheduling > monitoring agent watching for alerts and updates > coordinator agent routing tasks between all of them and he built a full 3D isometric office where you can watch all of them work in real time and see the current task that each agent is doing each agent has a character, a desk, and a name tag. when it's time for a standup, they walk to the meeting room and gather which is insane it even has voice connection. you can talk to the agents through speech-to-text and tell them what to do out loud it's a tiny autonomous team that runs itself. the coordinator decides who handles what and tasks get passed between agents automatically. it never stops and runs 24/7 all for less than $50/month. we went from AI tools a few months back to AI employees real fast
0:57

THIS GUY IS RUNNING A 5-AGENT OPENCLAW TEAM 24/7 FOR UNDER $50 A MONTH five agents all running continuously and handing tasks to each other > research agent tracking trends and competitors > writing agent handling marketing content and drafts > ops agent managing emails and scheduling > monitoring agent watching for alerts and updates > coordinator agent routing tasks between all of them and he built a full 3D isometric office where you can watch all of them work in real time and see the current task that each agent is doing each agent has a character, a desk, and a name tag. when it's time for a standup, they walk to the meeting room and gather which is insane it even has voice connection. you can talk to the agents through speech-to-text and tell them what to do out loud it's a tiny autonomous team that runs itself. the coordinator decides who handles what and tasks get passed between agents automatically. it never stops and runs 24/7 all for less than $50/month. we went from AI tools a few months back to AI employees real fast

Om Patel

27,131 görüntüleme • 4 ay önce

Today at Sessions, John Collison showed an agent acting as both buyer and seller in the same loop. Using Stripe Projects and Tempo Wallet, the agent: • Paid $0.04 for an Alpha Vantage dataset in stablecoins • Generated a research report • Listed it for sale to humans and agents
4:04

Today at Sessions, John Collison showed an agent acting as both buyer and seller in the same loop. Using Stripe Projects and Tempo Wallet, the agent: • Paid $0.04 for an Alpha Vantage dataset in stablecoins • Generated a research report • Listed it for sale to humans and agents

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33,465 görüntüleme • 3 ay önce

Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so you can get your real work done. Here's how we solved the AI context problem for hard engineering tasks (like rocket science 🚀) 🧵
2:19

Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so you can get your real work done. Here's how we solved the AI context problem for hard engineering tasks (like rocket science 🚀) 🧵

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1,552,492 görüntüleme • 6 ay önce

Unstructured intelligence = chaos Most agent frameworks ship without a nervous system: deadlocks, context loss, vacuum hallucinations. We built Common Ground to fix this, agents coordinate on a shared protocol.
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Unstructured intelligence = chaos Most agent frameworks ship without a nervous system: deadlocks, context loss, vacuum hallucinations. We built Common Ground to fix this, agents coordinate on a shared protocol.

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536,614 görüntüleme • 6 ay önce