AI coding agents now run for a long time. A single task can take hours: a refactor, a full test run, a migration. The question is no longer whether the model can finish the work, but where that work should run. Your laptop is fine for the first few minutes,
Giving an agent a filesystem, a shell, and a network hands generated code the same reach your laptop has. Here's how to package DeepAgents as a Docker Sandbox Kit that runs fully isolated against a local Docker Model Runner, with no cloud credentials and a one-command install.
I’ve been in the Docker community since 2015. I’ve written more docker run tutorials than I can count, and I still get people in the Collabnix Slack asking me which base image to use for their Spring Boot app. That question is still valid. But it is no
An AI-BOM is a machine-readable inventory of the models, datasets, prompts and agents your AI system depends on. Here is how it extends the SBOM you already ship
Docker Sandboxes 0.39 lets Claude Code's /remote-control run inside a microVM. Drive an isolated agent from your phone while your host filesystem stays out of reach. Here is how to turn it on, plus the credential requirement that trips up most first attempts.
A hands-on tour of the MCP gateway, kit spec v2, structured startup progress, per-sandbox network deny rules, and daemon restart introduced in Docker Sandboxes (sbx) 0.38.0.
Claude Code, like most agentic coding tools, asks for permission before it does anything consequential: editing a file, running a shell command, installing a package, or making a network call. That permission system is a safety rail. 💡"Yolo mode" is the community nickname for turning that rail off
Docker. Kubernetes. Agentic AI.
Rest isn't a reward. It's a part of how we work sustainably. Remote Life, Done Right ~ Docker
A technical deep dive into how Docker Sandboxes shares agent skills - the import flow, the persistent store, per-platform paths, the read-write trust boundary, and how it differs from shipping skills through a kit.
Here's a quick 9 tips for Sandboxing your AI agents with Docker Sandboxes Kits
Everything you want to know about the latest Docker sbx 0.35.0
Docker Model Runner supports three inference engines namely llama.cpp, vLLM, and Diffusers. Each engine has different strengths, supported platforms, and model format requirements. This blog article helps you in making a decision to choose the right engine and configure it for your use case.
Most developers running Claude Code today run it directly on their host machine. That means the agent shares an environment with your SSH keys, your AWS credentials, your browser sessions, and every other project on your laptop. A container helps, but a container is not a sandbox. A shared kernel
💡Updated for sbx v0.37.0-rc1. The SSH feature is still experimental and the command surface has moved since the first nightly builds. The examples below were re-run end to end on my own machine against v0.37.0-rc1, and every command here is verified working. If
Your weekly digest of Cloud-Native AI, Docker Sandboxes, and Model Context Protocol innovations.
Docker Sandboxes (sbx) runs your coding agent inside a microVM instead scoped to a single project directory, behind a network policy you control. Here's how to set it up on Windows, step by step.
Running an AI agent in a Docker Sandbox raises one question first: where do the API keys live. This hands-on guide wires the 1Password CLI into Docker Sandboxes so credentials resolve from your vault on demand and never sit in plaintext inside the container.
The Laptop is the New Prod
Run the Pi coding agent in an isolated microVM in about ten minutes, with your API key kept on the host and out of the agent's reach. A step-by-step walk through the official Pi kit for Docker Sandboxes.
