Grass
Gives your coding agent a dedicated VM that's ready 24/7
Grass launched on April 9, 2026 with 291 votes, #77 of 21,248 launches that month and more than 99% of that year's launches.
In plain words
Grass provides a dedicated virtual machine for coding agents that runs continuously without requiring setup or configuration. Developers can direct AI coding tools like Claude Code at the VM and monitor progress remotely from any device, making adjustments mid-session as needed. The service is designed for developers who want to run autonomous coding tasks without consuming local computing resources. New users receive 10 hours of free usage without needing a credit card.
written from the facts on this page · September 2026
From the sources
Grass gives your coding agent a dedicated VM that's always ready. No setup, no config, no burning your laptop. Point Claude Code or OpenCode at it and run. Monitor progress from your phone, steer mid-session, push changes, all without touching your machine. Every new account gets 10 hours free. No credit card needed.
Dispatch a task, close your laptop, pick it up when it
Dispatch a task from your iPhone. The agent runs on a persistent VM. Close the app and come back to results. Free to start. 10 hours on us. No card needed. It dies when you close the lid. It stalls when you lose connection. It waits when you can't approve a permission at 2am. The tool isn't the bottleneck. The infrastructure is. GrassVM, your Mac, your server. Switch between them in one tap without losing context. Sessions that outlast your attention span Fire a task, close your laptop, walk away. GrassVM keeps the session alive until the work is done. Added, modified, deleted, renamed. Per-line changes, repo-organized, navigable. Not a terminal wall of text. Stay in control without staying…from codeongrass.com
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1CodeJan 2026 · github.com · ▲569Just to clarify the background a bit. This project wasn’t planned as a big standalone release at first. On January 16, Ollama added support for an Anthropic-compatible API, and I was curious how far this could be pushed in practice. I decided to try plugging local Ollama models directly into a Claude Code-style workflow and see if it would actually work end to end. Here is the release note from Ollama that made this possible: https://ollama.com/blog/claude Technically, what I do is pretty straightforward: - Detect which local models are available in Ollama. - When…
Claude Code RoutinesApr 2026 · anthropic.com · ▲595Put Claude Code tasks on autopilot with smart routines
Skill that lets Claude Code/Codex spin up VMs and GPUsFeb 2026 · cloudrouter.dev · ▲138I've been working on CloudRouter, a skill + CLI that gives coding agents like Claude Code and Codex the ability to start cloud VMs and GPUs. When an agent writes code, it usually needs to start a dev server, run tests, open a browser to verify its work. Today that all happens on your local machine. This works fine for a single task, but the agent is sharing your computer: your ports, RAM, screen. If you run multiple agents in parallel, it gets a bit chaotic. Docker helps with isolation, but it still uses your machine's resources, and doesn't give the agent a browser, a desktop, or a GPU to…
ReplicasJun 2026 · replicas.dev · ▲239Hey HN! I'm Connor, creator of Replicas. I'm a heavy Codex/Claude Code user, and I wanted to hand off tasks to agents like I would to an engineer - kick something off before work, let it scaffold while I'm at lunch, even come back to a ready PR. The problem: existing alternatives use workspace VMs that are black boxes. I have no access to any of them - they can't run tests, read logs, or use tools like the Playwright MCP (which I use to verify agents actually fixed what they claim to fix). Replicas gives agents real cloud workspaces where they can: - Run your test suite and read the…
- Verdent Deck2025 · verdent.ai · ▲295
Hi HN! We just launched Verdent, an AI coding agent that actually plans before it codes, tests its own work, and delivers production-ready results without you having to clean up after it. tl;dr Check out the website [1] and read the story [2] - The problem: Current AI tools dump code and leave you to debug. You ask for "build a login endpoint" and get a passwordless JWT mess that doesn't fit your project. We've talked to hundreds of engineers who are frustrated with having to micromanage AI output. - What we built: Verdent works more like a senior engineer. It asks clarifying questions…
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