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Add memory to the agent you already use funes is a single binary. Its default inference backend has no ML runtime dependency, and embedding and reranking happen on your machine . Install it: Then add it to an agent: funes add claude or: codex, pi, hermes That one add command builds the first index, gives the agent recall and get tools, and installs the automation that indexes each completed turn. Indexing is incremental, with new runs adding new turns rather than embedding the whole history agai

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When we started designing Grok Bot, one of the central questions was how the interface should shape the relationship between user and agent. Most AI interfaces are organized around a chat session the user operates. Each session begins with setup, unfolds as the user looks on, and ends when the conversation stops. We wanted to design for an agent that persists beyond any one session and can carry responsibility on its own. That meant reconsidering some of the basic objects and signals of the inte

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Announcements You can safely connect your credit card and purchase things with hosted browser agents. Connect Link once. When the agent reaches a checkout it asks to pay, your phone buzzes, you approve, and Link hands it a virtual card good for exactly that purchase. The agent fills the form and pays. The card is gone after. Your real card number never leaves Link. How it works Connect Link once, under Integrations; The agent asks to pay. Amount, merchant, and what it is buying; You approve in t

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Table of Contents Control where agents execute; Workers connect your infrastructure to the Cursor agent loop; Cloud agents adapt to your infrastructure; Pools scale with demand and serve any repository; Workers run across supported sandbox providers; Agents control browsers on Linux and Mac; Bring cloud agents into your environment Cursor cloud agents can execute on dynamically scheduled pools of machines inside your network. You manage the underlying infrastructure, while agents are still start

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nd Program offerings bring together our most advanced cyber model, Gemini 3.8 Flash Cyber , with our CodeMender harness, to help defenders find, verify, and fix vulnerabilities at agentic scale. Spotting weaknesses creates awareness and fear; autonomously finding and fixing vulnerabilities delivers security. CodeMender with Gemini 3.8 Flash Cyber delivers the specialized reasoning to write and validate code fixes, at a fraction of the operating cost of traditional frontier models. Instead of tak

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ind Program offerings bring together our most advanced cyber model, Gemini 3.8 Flash Cyber, with our CodeMender harness, to help defenders find, verify, and fix vulnerabilities at agentic scale. Spotting weaknesses creates awareness and fear; autonomously finding and fixing vulnerabilities delivers security. CodeMender with Gemini 3.8 Flash Cyber delivers the specialized reasoning to write and validate code fixes, at a fraction of the operating cost of traditional frontier models. Instead of tak

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realistic or cost-effective. The Rundown: 56% of consumers can spot AI-generated content. 40% say it's eroding their trust in your brand. To solve this, Corinthia Hotels built a 7-agent AI ecosystem to execute personalization across 5 personas, 14 lifestyle stages, over 75 behavioural signals, and 6,000+ content variants without sacrificing brand standards. Join Optimizely’s upcoming webinar on Oct. 7th to: Hear how they hit a 100% brand approval rate, achieved 10x productivity, and saved 150+ h

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hatsApp. At the same time, businesses with conventional phone numbers often have years of call flows already built on Twilio. Both groups kept asking us the same question: can our agent answer there, without rebuilding our telephony around a SIP trunk? Today the answer is yes. We're launching LiveKit Connectors, a direct bridge between LiveKit rooms and the platforms people already call — Twilio Programmable Voice and WhatsApp Business Calling to start, with more on the way. A connector brings t

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ai and ml Making installation easier and putting a new wrapper on the interface while leaving most of the security to users is a recipe for more trouble with the popular agent harness MOST POPULAR Anthropic asks users to stop being mean to Claude; '123456' password linked to Denmark data breach affecting 8.8M people; Intel optimizes IPv6 networking into nothingness, say users; When you just need to build a tiny desktop app: TinyJS; No shame in the Domain Name game: DNS is doomed, literally OpenC

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ew pricing anytime in your Ollama account settings. Every plan includes: High-performance access to the latest open models, at published per-token rates; Works with popular coding agents, including Claude Code and Codex, plus an API for your own tools; Monthly usage credits included with every plan; Zero data retention, hosted in the US and Europe; No service fees or hidden limits New plans Ollama’s new Pro, Max, and Team plans include a pool of usage credits that refreshes every month. Usage is

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Prepare your wallets! Grok Bot can now buy things. Excited to bring more superpowers to @bot to help you do all the things on your todo list (and on an personal note very full circle moment for me going from agentic commerce @stripe -- building payments into Grok Bot! very fun working with the Stripe team on this.)

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We’re opening a research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, to a first group of scientific research labs and advanced manufacturers. MHS enables AI agents to operate multiple lab and manufacturing instruments, such as microscopes, liquid handlers, and robotic arms, in parallel, and perform intricate tasks ranging from routine drug discovery experiments to laser calibration on a quantum computer. The development o

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stack, context-rich apps that combine live Databricks warehouse data with information created and updated through the app. When an app built with Replit is ready to deploy, Replit Agent automatically provisions its Lakebase database, eliminating the need for manual setup. Automated Preview Deploys: Test your apps before they go live. Replit automatically creates a separate preview environment that keeps test data isolated from live business data in Databricks, giving teams a safe place to build,

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arch.text'); sessionStorage.removeItem('facets.search.text-copy'); sessionStorage.removeItem('facets.search.filters'); Experiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding Qwen3.8-Flash-Next is a multimodal mixture-of-experts model with 125B parameters, 6B activated per token, and a native 262,144-token context window extensible to 1M tokens with YaRN. The architecture combines Gated DeltaNet and Qwen Sparse Attention, where three of every four layers use GDN to compress h

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ption is changing specific model weights or activations and observing how that affects the model’s output. Silico combines a broad range of these tools, and provides a layer of AI agents to help users understand their model. Users describe what they want to investigate about their AI model in plain language, asking things like ”Find out when and why my model is hallucinating.” The platform then autonomously builds an experimental plan involving a host of tasks that can be performed using the var

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skips images, say: “Use photos in this artifact” Pro tip: “Static site” is the keyword for portfolios, landing pages, and mockups. It keeps the complexity way down for you and the agent. The Rundown: Scribe Optimize automatically maps how work actually happens across your org — so before you build an AI strategy, you're working from reality, not assumptions. With Scribe Optimize, you can: Map real workflows — no surveys or consultants Surface inefficiencies leadership can't currently see Build y

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Today, we’re excited to announce that Grok 4.6 is now available on Microsoft Foundry. Grok 4.6 is our latest flagship model, built for long-running agents and ambitious interactive and visual work. It offers a 500k context window and configurable reasoning efforts (low, medium, high, xhigh). For more on the model, read the Grok 4.6 announcement . Build with Grok 4.6 on Microsoft Foundry Foundry gives organizations a single place to evaluate Grok 4.6 against other frontier models, run workload-sp

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ast year, so we could test it while also shoring up our defenses against prompt injection : malicious instructions hidden in websites, emails, or documents that try to trick an AI agent into acting against the user’s wishes. These defenses, described below, give us the confidence to make Claude in Chrome generally available. Safeguarding against prompt injection As we outlined when we announced the pilot, an AI agent that works in your browser is also vulnerable to prompt injection. So we’ve wor

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laude uses the built-in browser. Switch anytime in Settings → Cowork → Preferred browser. Staying in control The built-in browser carries the same prompt injection risks as any AI agent that acts in a browser, where instructions hidden in a page try to redirect Claude. It runs the same safeguards as Claude in Chrome, including the checks that review Claude's actions against what you asked for. We describe them on the Claude in Chrome blog post . Those measures meaningfully reduce the risk but ca

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, separate from your Grok and Cursor plans, so anything you hand off to a Bot won't count against your existing usage. Give Bots real work Grok Bot is designed for people who want agents to handle anything from a project to an entire function. They're digital teammates you can message, run in parallel, and trust to finish work in the tools you already use. Bots work across apps and inboxes, keep going when you step away, and only pull you in for judgment calls. With Grok Bot, you get: A text-thr

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