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Most engineering teams run AI coding agents on individual laptops. Close the lid, lose the session. When a new developer joins, they spend hours recreating the same setup.
CloudCLI gives your team shared cloud environments where AI agents run 24/7. Every developer gets their own isolated container, but the team shares MCP servers, context files, and configurations across all projects. Onboarding takes minutes.
Sessions can be started through a full REST API, so workflows in Linear, Jira, or n8n can trigger background coding agents programmatically. A ticket gets filed, an agent starts coding, the developer reviews the PR in the morning.
The web UI and mobile interface include a file explorer, git explorer, and full shell access. Review PRs on your iPad, make fixes from your phone, then pick up in VS Code over SSH.
Unlike GitHub Codespaces, CloudCLI is purpose-built for agentic development. Claude Code, Cursor CLI, Codex, and Gemini CLI come pre-installed. Sessions survive laptop closure. Teams bring their own API keys with no vendor lock-in.
Built on an open-source core (AGPL-3, 9,000+ GitHub stars). Self-host for data sovereignty or use the managed service from €7/month.
CloudCLI
MediumMedium is recommended for avid readers seeking a variety of topics ranging from personal development to technology. It's also ideal for writers looking to publish their work to a broad audience and potentially earn revenue through the platform's Partner Program.
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CloudCLI's answer
CloudCLI is built with a modern JavaScript/TypeScript stack:
The entire codebase is open source under AGPL-3 and available on GitHub.
CloudCLI's answer
Compared to tools like GitHub Codespaces, CloudCLI is purpose-built for agentic development rather than traditional coding. Here's what sets it apart:
CloudCLI's answer
CloudCLI is one of the only cloud development environments built specifically for AI coding agents. Where Codespaces and Gitpod give you a cloud editor, CloudCLI gives your agents a persistent home that stays alive 24/7. What makes it particularly valuable for teams: shared MCP servers and environment configs mean every developer starts from the same baseline. A full REST API means sessions can be triggered from automation tools, not just opened manually. Background agents can run overnight and produce PRs for review in the morning. And the entire platform is open source (AGPL-3) so teams can self-host on their own infrastructure.
CloudCLI's answer
CloudCLI is built for engineering teams that use AI coding agents as part of their daily workflow. This includes teams adopting agentic development practices with tools like Claude Code, Cursor CLI, or Codex who need shared environments where MCP servers, context files, and configurations stay consistent across every developer. It also serves engineering managers looking to integrate AI agents into existing workflows through API-driven automation with tools like Linear, Jira, and n8n. Solo developers and open-source contributors who want persistent remote access from any device are also a core audience, along with organizations that need to self-host for data sovereignty or regulatory compliance.
CloudCLI's answer
CloudCLI started as an open-source project to solve a problem every developer using AI coding agents hits: your agent ties up your terminal and stops working when your laptop sleeps. We built a cloud-native environment where agents run persistently, paired with an open-source web UI so anyone could manage sessions from a browser or phone. As teams started adopting it, the focus shifted to shared environments, where team-wide MCP servers, configurations, and context files could be maintained in one place instead of duplicated across every developer's machine. The project grew to 9,000+ GitHub stars organically with no marketing. Today CloudCLI offers both a free self-hosted option and a managed cloud service starting at €7/month.
Based on our record, Medium seems to be more popular. It has been mentiond 3125 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
That's the ratio the widely published numbers give [1][2]. One does not have to believe the numbers, of course, but those who do believe them are then justified to conclude that there's no moat. Which numbers you believe is of course going to affect whether you think there's a moat or not. [1] https://galileo.ai/blog/llm-model-training-cost [2]... - Source: Hacker News / about 11 hours ago
Kent Beck called this “test && commit || revert” in 2018, and credits Oddmund Strømme for first coming up with the idea: . - Source: Hacker News / 1 day ago
Https://medium.com/@ashishrathour1102 Looking for backend, infrastructure, platform, distributed-systems, storage-engine, or systems-programming roles. Especially interested in small/high-ownership teams working on runtimes, execution infrastructure, databases, developer infrastructure or reliability. - Source: Hacker News / 3 days ago
I kept generating documentation with an agent, and weeks or months later it would quietly go stale. Updating it was the costly part: either let an agent re-scan the whole repo, or sit there trying to remember what changed. So I made the deck carry its own provenance. SlideOps turns a repo into a slide deck, and every claim in that deck records the file it came from, the exact line range, and a hash of those lines.... - Source: Hacker News / 4 days ago
Maybe you could use something like this to make it real: > Building a Real-Time Concentration Tracker using MediaPipe and OpenCV > A simple AI project that measures focus and attention using your webcam — with Python, OpenCV, and MediaPipe. https://medium.com/@jiyasisdiya/building-a-real-time-concentration-tracker-using-mediapipe-and-opencv-2da7384ace24. - Source: Hacker News / 11 days ago
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