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Agent development is moving forward. While production scaling traditionally required manual infrastructure setup and provisioning sandboxes from scratch, there's now a faster path. Managed Agents in the Gemini API are officially live. Get maximum agentic power with zero infrastructure overhead. One simple API call delivers a managed, remote sandbox...

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Google for Developers

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38,142 görüntüleme • 10 gün önce •via X (Twitter)

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Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.
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Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.

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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
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Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

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Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio
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Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio

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What if you can build an Agent with it own computer in a single api call? At my Google I/O talk, I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory.
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What if you can build an Agent with it own computer in a single api call? At my Google I/O talk, I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory.

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🚨 The $TMAI API is Now Live. Signals, grades, analytics — Now available for you to build trading agents, dApps, and more. The same data we use. Now all in your hands. Get started for FREE:
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🚨 The $TMAI API is Now Live. Signals, grades, analytics — Now available for you to build trading agents, dApps, and more. The same data we use. Now all in your hands. Get started for FREE:

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Gemini models are now accessible to millions of Apple developers through Apple’s Foundation Models framework and natively within Xcode. You can now easily swap between local and cloud inference using a shared API surface to build next-generation agentic app experiences, increase development velocity, and offload heavy workloads to the cloud. Additionally, you can use agentic coding assistance from Gemini in Xcode to accelerate multi-step development tasks. Check out the full announcement to get started:
4:05

Gemini models are now accessible to millions of Apple developers through Apple’s Foundation Models framework and natively within Xcode. You can now easily swap between local and cloud inference using a shared API surface to build next-generation agentic app experiences, increase development velocity, and offload heavy workloads to the cloud. Additionally, you can use agentic coding assistance from Gemini in Xcode to accelerate multi-step development tasks. Check out the full announcement to get started:

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🚀 Micro Agent is now live on the PAAL AI 🧠🤖 Agents Marketplace! 🎉 Developers can now interact with Micro Agent via API to build powerful apps and integrate with other agents seamlessly. Unleash the full potential of AI! 👉 Explore:
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🚀 Micro Agent is now live on the PAAL AI 🧠🤖 Agents Marketplace! 🎉 Developers can now interact with Micro Agent via API to build powerful apps and integrate with other agents seamlessly. Unleash the full potential of AI! 👉 Explore:

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your agents can now get paid and spend money. create a wallet and a budget for every agent. you are now in control. ampersend is live. use or add the skill to your OpenClaw🦞
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your agents can now get paid and spend money. create a wallet and a budget for every agent. you are now in control. ampersend is live. use or add the skill to your OpenClaw🦞

ampersend

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getting started with managed agents in ai studio and the gemini api a guide by Patrick Loeber:
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getting started with managed agents in ai studio and the gemini api a guide by Patrick Loeber:

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Claude Managed Agents can operate in a sandbox you control, on your own infrastructure or with any provider you choose. Today we added new guides for Blaxel, E2B, Google Cloud, Namespace, and superserve.ai, so you can choose the best fit for your use case.

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today, we are making the Mosaic video editing api available to all agents & humans. see how we setup larry — our slack openclaw agent — with a mosaic api key and had it clip, edit, and post archived steve jobs footage. all without ever leaving slack. you can connect your openclaw agents, claude code, or vibe-coded saas to our agentic video editing api. no waitlist — now live at mosaic [dot] so. comment "API" to get 100 free credits dropped into your account to get started with the api for free. more details on why & how we’re making this change below (thread):
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today, we are making the Mosaic video editing api available to all agents & humans. see how we setup larry — our slack openclaw agent — with a mosaic api key and had it clip, edit, and post archived steve jobs footage. all without ever leaving slack. you can connect your openclaw agents, claude code, or vibe-coded saas to our agentic video editing api. no waitlist — now live at mosaic [dot] so. comment "API" to get 100 free credits dropped into your account to get started with the api for free. more details on why & how we’re making this change below (thread):

Adish Jain ☕️

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In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11
43:20

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11

Dan Shipper 📧

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the security and control of Ledger the payments and ramps infrastructure of MoonPay now compatible with the Agentic Economy via a simple CLI live now for agents everywhere 🤖🔐🤖🔐
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the security and control of Ledger the payments and ramps infrastructure of MoonPay now compatible with the Agentic Economy via a simple CLI live now for agents everywhere 🤖🔐🤖🔐

MoonPay 🟣

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OptimAI Search is now on Agentic(.)Market - and we’re bringing the stack to Base. Builders can plug into live, citation-backed context across web, social, and crypto data through MCP, API, and SDK - then pay seamlessly with x402. No brittle workflows. No manual stitching. Just agent-native access to real-time intelligence at scale. And with custom domain agents on the marketplace, specialized knowledge becomes reusable. Search is becoming infrastructure. Build with it: 💡 💡

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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
3:38

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

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Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:
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Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:

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Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:
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Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:

OKX

34,781 görüntüleme • 3 ay önce

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.
1:51

Introducing Base44 Superagents. AI agents built with managed infrastructure, secured by default, one-click integrations, and 24/7 execution from the start. Everything is taken care of so you can focus on what your agent does, not how to get it running. That means no API keys to juggle, no config files, no security setup, and no maintenance. We handle all of it. Your Superagent connects to all the tools you already use in one click, runs on schedules and triggers, remembers context across sessions, acts proactively on your behalf, and keeps working around the clock. All from wherever you already are, WhatsApp, Telegram, Slack, or your browser. The AI agent everyone's been waiting for, with everything you need already built in. We're excited to get this into your hands, so we're giving free credits to everyone who comments and reposts in the next 24 hours.

Base44

1,577,081 görüntüleme • 3 ay önce

It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!
1:46

It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!

elvis

45,690 görüntüleme • 10 ay önce

the ai platform war is coming Kieran Klaassen and i recorded a quick dispatch from code with Claude on the xAI compute deal, managed agents, and why anthropic is turning their api into a full cloud infrastructure for developers:
9:48

the ai platform war is coming Kieran Klaassen and i recorded a quick dispatch from code with Claude on the xAI compute deal, managed agents, and why anthropic is turning their api into a full cloud infrastructure for developers:

Dan Shipper 📧

13,519 görüntüleme • 1 ay önce