Tutorial

Cloudflare’s Agents Week brought two tools that, combined, solve one of the most persistent infrastructure problems in production agentic AI: how do you run agents that actually do work across multiple sessions without losing state? This guide walks through building a persistent long-running agent using Cloudflare’s GA Linux Sandboxes and the Think SDK. Both are now generally available — meaning this is production-ready infrastructure, not a preview. What You’re Building A persistent agent that can: ...

Anthropic’s Claude Managed Agents entered public beta on April 8, 2026. If you’ve been waiting for a managed platform to deploy Claude-powered agents without standing up your own infrastructure, this is it. Here’s how to get started. Prerequisites Before you begin, you’ll need: An Anthropic API account (platform.anthropic.com) Access to the Managed Agents beta (apply at the developer platform) Basic familiarity with REST APIs or the Anthropic Python/TypeScript SDK Python 3.10+ or Node.js 18+ for the examples below Step 1: Apply for Beta Access Navigate to platform.claude.com and look for the Managed Agents section. As of the public beta launch, this is open to teams — not just individual developers. You’ll want to apply with your organization’s use case described, as Anthropic appears to be prioritizing enterprise workloads. ...

MolmoWeb is Ai2’s open-source browser agent — 8B parameters, Apache 2.0, no API key required. It scores 78.2% on WebVoyager and beats GPT-4o-based agents on multiple benchmarks. Here’s how to get it running locally. System requirements: GPU with at least 16GB VRAM (for 8B model) or 8GB VRAM (for 4B model) Ubuntu 20.04+ or macOS 12+ (Linux recommended for GPU support) Python 3.10+ Chrome or Chromium browser installed Step 1: Clone the Repository git clone https://github.com/allenai/molmoweb.git cd molmoweb Step 2: Create a Virtual Environment and Install Dependencies python3 -m venv molmoweb-env source molmoweb-env/bin/activate pip install -r requirements.txt The requirements include PyTorch, the Transformers library, Playwright for browser control, and Pillow for screenshot processing. The full install typically takes 3–5 minutes on a good connection. ...

Claude Code Ultraplan offloads your most complex planning tasks to a cloud Opus 4.6 session for up to 30 minutes — while you keep working locally. Here’s how to use it in five steps. Prerequisite: Ultraplan requires the $400/month Claude Code plan tier. Step 1: Open Ultraplan from the Command Palette In Claude Code, open the command palette (Cmd/Ctrl + Shift + P) and type Ultraplan. Select “Claude Code: Start Ultraplan Session”. ...

AIO Sandbox from Agent-Infra packages everything an AI agent needs to operate — browser, shell, filesystem, MCP server, VSCode, and Jupyter — into a single Docker container. Here’s how to get it running in under 5 minutes. Prerequisites Docker installed and running (get Docker) Port 8080 available on your machine ~2GB free disk space for the container image Step 1: Pull and Run the Container docker run --security-opt seccomp=unconfined --rm -it -p 8080:8080 ghcr.io/agent-infra/sandbox:latest The --security-opt seccomp=unconfined flag is required for browser automation to work inside the container. The first run will pull the image (~1-2GB), subsequent starts are fast. ...

Your LangGraph agent works perfectly in development. Then it hits production and you discover the problem every agent developer eventually hits: when the process restarts, your agent remembers nothing. In-memory state is fine for demos and local testing. For production agents — especially those handling multi-step workflows that can span hours, serve concurrent users, or need to resume after infrastructure failures — you need persistent state. This guide walks through adding Aerospike Database 8 as a durable memory store for your LangGraph agent. ...

If your Claude Code usage limits are draining faster than you expect, you’re not imagining it and you’re not hitting a bug. Anthropic confirmed this week that usage consumed during peak hours counts at an accelerated rate against your monthly limit. The peak window: 5:00 AM to 11:00 AM Pacific Time, Monday through Friday. This guide covers what that means for your usage, how to track where your limit is going, and the practical strategies that actually help. ...

Full autonomy is the goal for many agentic workflows — but full autonomy is also where most production deployments fail their first risk review. The practical path to deploying AI agents in real organizations runs through human-in-the-loop (HITL) patterns: workflows where the agent does the work, humans approve the decisions, and the system handles the handoff cleanly. LangGraph has strong native support for HITL patterns through its interrupt primitives. This guide walks through the core patterns — interrupt points, approval gates, and reversible actions — with working code you can adapt for your own agent workflows. ...

Getting OpenClaw running locally has always required a non-trivial amount of setup — installing dependencies, configuring models, managing environment variables, and keeping the stack running reliably. With the launch of FlashClaw today, there’s now a one-click cloud path that skips all of that. This guide walks you through getting your first OpenClaw agent running in the cloud using FlashClaw, from account creation to your first autonomous workflow. What You’ll Need A FlashClaw account (sign up at flashclaw.dev) An API key for your preferred AI model (OpenAI, Anthropic, xAI Grok, or others supported by OpenClaw) A workflow idea — even something simple like “monitor a URL and summarize changes daily” works perfectly for a first test Time required: 10–15 minutes for your first deployment. ...

JetBrains Air entered public preview today — an agentic IDE built on the Fleet codebase that supports running multiple AI coding agents in parallel. If you’ve been following the agentic IDE space and want to get hands-on, this guide walks through installation, initial configuration, and your first parallel agent workflow. Prerequisites Before you start, confirm you have: A JetBrains account — Air requires a JetBrains account, even in public preview. Free accounts work during the preview period. JetBrains AI subscription (optional for basic use, required for premium models) — if you want to use Claude or GPT-5 as your underlying model, you’ll need a JetBrains AI subscription. The default model (JetBrains’ own hosted model) is available free during preview. System requirements: macOS 13+, Windows 11, or Ubuntu 22.04+. M1/M2/M3 Mac or Windows ARM is recommended for performance. 16GB RAM minimum, 32GB recommended for larger codebases. Step 1: Download and Install Air Go to jetbrains.com/air and click Download Public Preview You’ll be prompted to log in to your JetBrains account Download the installer for your platform Run the installer — Air installs independently from other JetBrains IDEs and does not replace or affect IntelliJ IDEA, PyCharm, or other products The install is straightforward. Air does not use the JetBrains Toolbox App for management during the preview period — it’s a standalone installer. ...