The company says you can use plug-ins to "tell Claude how you like work done, which tools and data to pull from, how to handle critical workflows, and what slash commands to expose so your team gets more consistent outcomes."
Agentic AI is causing a transformative shift in cloud operations by going far beyond scripted automation to offer autonomous orchestration of complex tasks.
Moltbot, a personal AI assistant being run on batches of Mac minis, got a lot of attention when creator Matt Schlicht effectively partnered with his own assistant to develop a social media platform for the bots. Known as Moltbook, it’s been colloquially referred to as Reddit for AI bots. Schlicht
Enterprise AI is shifting fast from chatbots that answer questions to systems that actually do the work across an organization. But who will own the AI layer that powers all of it?  Glean, which started as an enterprise search product, has evolved into what it calls an “AI work assistant,” aimi
Enterprise AI is shifting fast from chatbots that answer questions to systems that actually do the work across an organization. But who will own the AI layer that powers all of it?  Glean, which started as an enterprise search product, has evolved into what it calls an “AI work assistant,” aimi
In this week's episode of the Equity podcast, Glean CEO Arvind Jain explains the company's shift from enterprise search tool to middleware layer for enterprise AI.
The viral X post from an AI security researcher reads like satire. But it's really a word of warning about what can go wrong when handing tasks to an AI agent.
Nimble uses AI agents to search the web, verify and validate the results, and then clean and structure the information into neat tables that can then be queried like a database.
The company said that a new agent being introduced in Opal will allow users to create mini-apps that can let them plan and execute tasks using text prompts.
Seattle-based Vercept developed complex agentic tools, including a computer-use agent that could complete tasks inside applications like a person with a laptop would.
Trace is launching with $3 million in seed funding, including investment from Y Combinator, Zeno Ventures, Transpose Platform Management, Goodwater Capital, Formosa Capital, and WeFunder.
Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv and feedback from readers. If you’d like to support this, please subscribe. Subscribe now The AGI economy – most labor goes to the machines, and humans shift to verification:…What grappling with the singularity seriously l
AgentMail provides an API platform that lets you give AI agents their own email inboxes, with support for two-way conversations, parsing, threading, labeling, searching, and replying.
Meta’s Moltbook acquisition may look odd at first, but the deal could signal how Meta sees AI agents shaping future advertising and commerce on an agentic web.
As companies race to adopt AI, Benchmark general partner Everett Randle believes the key to success lies in empowering every worker with AI superpowers, and Gumloop’s intuitive agent builder is an example of the kind of tool that will unlock that potential.
NVIDIA's GTC 2026 (March 10-14) marked a shift from AI demonstrations to production deployment case studies, with Fortune 500 companies presenting live agentic AI systems in active use. OpenCLAW surpassed 100,000 GitHub stars, making it the fastest-growing open-source AI project on record. NeMoCLAW and OpenCLAW emerged as the dominant orchestration frameworks across enterprise announcements at the conference.
Meta’s Ranking Engineer Agent (REA) autonomously executes key steps across the end-to-end machine learning (ML) lifecycle for ads ranking models. This post covers REA’s ML experimentation capabilities: autonomously generating hypotheses, launching training jobs, debugging failures, and iterating on
Nothing CEO Carl Pei says AI agents will eventually replace apps, shifting smartphones toward systems that understand intent and act on a user's behalf.
Kimi K2.5 is now on Workers AI, helping you power agents entirely on Cloudflare’s Developer Platform. Learn how we optimized our inference stack and reduced inference costs for internal agent use cases.
Autonomous agents mark a new inflection point in AI. Systems are no longer limited to generating responses or reasoning through tasks. They can take action: Agents can read files, use tools, write and run code, and execute workflows across enterprise systems, all while expanding their own capabiliti
We’re introducing Dynamic Workers, which allow you to execute AI-generated code in secure, lightweight isolates. This approach is 100 times faster than traditional containers, enabling millisecond startup times for AI agent sandboxing.
Anthropic's Model Context Protocol reached 97 million installs as of March 2026, with all major AI providers now shipping MCP-compatible tooling. The Linux Foundation announced it will take the protocol under open governance, removing single-vendor control. MCP has become the de facto standard for AI tool interoperability in under two years of existence.
Granola's valuation jumped from $250 million to $1.5 billion with this round, and it has added more support for AI agents after users previously complained.
Meta continues to lead the industry in utilizing groundbreaking AI Recommendation Systems (RecSys) to deliver better experiences for people, and better results for advertisers. To reach the next frontier of performance, we are scaling Meta’s Ads Recommender runtime models to LLM-scale & complexity t
This is the second post in the Ranking Engineer Agent blog series exploring the autonomous AI capabilities accelerating Meta’s Ads Ranking innovation. The previous post introduced Ranking Engineer Agent’s ML exploration capability, which autonomously designs, executes, and analyzes ranking model exp
AI coding assistants are powerful but only as good as their understanding of your codebase. When we pointed AI agents at one of Meta’s large-scale data processing pipelines – spanning four repositories, three languages, and over 4,100 files – we quickly found that they weren’t making useful edits qu
Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, people, and other agents in real time, AI agents can execute entire workflows autonomously. But unlocking their potential requires redesigning processes around age
If you've ever watched two agents confidently write to the same resource at the same time and produce something that makes zero sense, you already know what a race condition feels like in practice.
A new open-source toolkit from Microsoft focuses on runtime security to force strict governance onto enterprise AI agents. The release tackles a growing anxiety: autonomous language models are now executing code and hitting corporate networks way faster than traditional policy controls can keep up.
Next-generation AI assistants being developed in the Apple ecosystem and by chipmakers like Qualcomm, but early reports suggest they are being designed with limits in place. Tom’s Guide has described early versions of these assistants as capable of navigating apps, carrying out bookings, and managin
In this tutorial, we build and operate a fully local, schema-valid OpenClaw runtime. We configure the OpenClaw gateway with strict loopback binding, set up authenticated model access through environment variables, and define a secure execution environment using the built-in exec tool. We then create
Cloudflare's mission has always been to help build a better Internet. Sometimes that means building for the Internet as it exists. Sometimes it means building for the Internet as it's about to become. This week, we're kicking off Agents Week, dedicated to what comes next.
MiniMax, the AI research company behind the MiniMax omni-modal model stack, has released MMX-CLI — Node.js-based command-line interface that exposes the MiniMax AI platform’s full suite of generative capabilities, both to human developers working in a terminal and to AI agents running in tools like
Cloudflare Sandboxes give AI agents a persistent, isolated environment: a real computer with a shell, a filesystem, and background processes that starts on demand and picks up exactly where it left off.
We’re introducing Durable Object Facets, allowing Dynamic Workers to instantiate Durable Objects with their own isolated SQLite databases. This enables developers to build platforms that run persistent, stateful code generated on-the-fly.
In this tutorial, we build an advanced data analysis pipeline using Google ADK and organize it as a practical multi-agent system for real analytical work. We set up the environment, configure secure API access, create a centralized data store, and define specialized tools for loading data, exploring
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