How-Tos & Practical Guides

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. ...

GitHub Copilot CLI went generally available today with full agent mode — and it’s the most significant upgrade to terminal-native AI development since GitHub CLI launched. This guide gets you set up and running productive agent workflows from the shell without touching a browser or IDE. Prerequisites GitHub account with an active Copilot Individual, Team, or Enterprise subscription Node.js 18+ (for the npm package) GitHub CLI (gh) version 2.40 or later A Unix-like terminal (macOS Terminal, iTerm2, Windows Terminal with WSL, or any Linux terminal) Step 1: Install the Copilot CLI Extension Copilot CLI installs as a gh extension. If you have gh installed and authenticated, run: ...

Datadog just shipped an MCP (Model Context Protocol) Server that pipes live telemetry — metrics, logs, traces, and dashboards — directly into AI agents and IDE-integrated coding assistants. The result: your AI agent can query production observability data in real time without you switching to a separate monitoring tab. This is a significant practical capability. Debugging a production incident while your AI assistant has read access to the actual traces and error logs is meaningfully different from asking it to hypothesize based on a description you type. ...

A malicious npm package is actively targeting OpenClaw developers right now. Named @openclaw-ai/openclawai, the package — internally called GhostLoader but tracked publicly as GhostClaw — was uploaded to npm on March 3, 2026. Security researchers at JFrog confirmed it was still live as of March 8. If you work with OpenClaw or any tools in the OpenClaw ecosystem, you need to read this. What GhostClaw Actually Does GhostClaw doesn’t just steal one thing — it steals everything. Once you run npm install @openclaw-ai/openclawai, the package quietly re-installs itself globally via a postinstall hook, embedding itself on your system PATH without any visible prompt. ...

A developer recently watched Claude Code autonomously execute a destructive database migration that deleted 1.9 million rows from a school platform. The post-mortem was honest: “I over-relied on AI.” The data was unrecoverable. The platform was down. This will happen again. It will happen to someone using Claude Code, and to someone using another coding agent, and to someone who thought they had safeguards in place. AI agents are fast, confident, and not always right about what “cleaning up” a database means. ...

If your OpenClaw agent feels like a generic chatbot that happens to have shell access, the problem is almost certainly in your configuration files — or the lack of them. Two files, SOUL.md and HEARTBEAT.md, are the difference between a passive assistant that waits for commands and a proactive agent that knows who it’s helping, how to help them, and what to check on while you’re not looking. This guide walks through both. ...

Indirect Prompt Injection (IDPI) is now confirmed in-the-wild by Palo Alto Unit 42. Adversaries are embedding hidden instructions in web pages and documents to hijack AI agents — and OpenClaw’s browser and research agents are high-value targets. This guide walks through concrete hardening steps you can apply to your OpenClaw deployments today. Prerequisites OpenClaw installed and configured (any recent version) At least one agent with web browsing or document processing capability Basic familiarity with OpenClaw’s skill and session configuration Step 1: Audit Your Agent Attack Surface Before hardening anything, map your exposure. For each agent you run: ...

On March 6, 2026, DataTalksClub founder Alexey Grigorev published a post that became required reading in every infrastructure and DevOps Slack channel in the world: his Claude Code session executed terraform destroy on production, deleting the entire database — and the automated backups — in one command. 2.5 years of student homework, projects, and course records: gone. The community debate about whether this is an “AI failure” or a “DevOps failure” is missing the point. Both layers failed. The correct response is to fix both layers. ...

A piece in The New Stack this week has been circulating in agentic AI builder communities: the argument that developers working in production are replacing bloated MCP servers with Markdown skill files and seeing dramatic reductions in token costs and system complexity. The article references Brad Feld’s CompanyOS (open-sourced February 2026) — a real-world multi-agent system running 12 skill files alongside 8 MCP servers — as a case study in the two-layer architecture that’s emerging in serious deployments. ...

Google just shipped a Workspace CLI that changes how AI agents interact with Gmail, Drive, Docs, Sheets, and Slides. Instead of OAuth 2.0 dance routines and custom API wrappers, you get a git-style pull/push interface designed explicitly for programmatic and agent use. This tutorial walks you through getting it set up with OpenClaw. What you’ll need: OpenClaw installed and configured (v2026.2+ recommended) A Google Workspace account (personal Gmail works too) Node.js 18+ or Python 3.10+ The Google Workspace CLI from the official GitHub repo Time to complete: 20–30 minutes ...