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HolyCode Cloud is a cloud AI workstation with 60+ tools already installed, built for running AI coding agents unattended.
Hand off a task, close your laptop, and the work continues. Processes, files and terminal scrollback survive the disconnect, and the machine suspends when idle and resumes in about a second, so an always-on workspace does not bill like one.
Six agent CLIs preinstalled and on PATH: Claude Code, Codex, Gemini, OpenCode, Cursor and Pi.
Plus the tooling agents actually reach for: Postgres, Playwright with its system dependencies resolved, ffmpeg, pandoc, gh, ripgrep, tmux, Node and Python with build-essential.
Bring your own key. Your Anthropic, OpenAI or Gemini key stays on your box. The provider bills you directly and there is no markup on tokens.
Most cloud dev environments are containers with an idle reaper that reclaims them when nobody has typed for a while, which is exactly what a working unattended agent looks like to a timer. Here the workspace is a real VM with a persistent disk.
Five tiers from $19 to $199 per month, differing only by CPU, RAM and disk. Every feature is on every tier. No free tier; a 7-day refund instead, with no form and no call.
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HolyCode's answer:
The machine does not stop when you do. Most cloud dev environments are containers with an idle timer that reclaims them when nobody has typed for a while, which is exactly what a working unattended agent looks like to a timer. Here the workspace is a real VM with a persistent disk. Hand an agent a four-hour task, close your laptop, and the processes, files and terminal scrollback are still there when you come back. It suspends when idle and resumes in about a second, so always-on does not mean always-billing.
HolyCode's answer:
Three practical differences. First, nothing gets reclaimed for idleness, so long unattended agent runs actually finish. Second, every tier includes the full toolset. Tiers differ only by CPU, RAM and disk, so paying more buys horsepower rather than unlocking features. Third, you bring your own Anthropic, OpenAI or Gemini key and the provider bills you directly, with no markup on tokens.
Where it is not the right choice: if you want a free tier to try, there isn't one, because every account is a real VM that costs money from the first minute. There is a 7-day refund instead.
HolyCode's answer:
Developers running AI coding agents on real work rather than demos. Typically people who already pay for Claude, Codex or Gemini and have hit the point where the bottleneck is not the model but the machine underneath it. Many have tried tmux on a VPS and got tired of maintaining the VPS.
HolyCode's answer:
It started as an open-source Docker image for running coding agents with persistent state, which is still free and maintained at github.com/CoderLuii/HolyCode. The most common feedback was that persistence mattered most: sessions, settings and progress surviving a rebuild rather than starting over each time. The hosted version is that same image on a machine someone else maintains.
HolyCode's answer:
Fly.io machines with persistent volumes for the workspaces, Docker and Debian for the image, ttyd for the browser terminal, Node and React for the interface, and Cloudflare for the site and control plane.
GitHub is an essential platform for modern software development. It makes it easy to host, manage, and collaborate on code while providing powerful tools for version control, project management, and team collaboration. Its large open-source community is another major strength, offering developers access to countless projects, resources, and opportunities to learn. Overall, GitHub is a reliable and professional platform that has become a fundamental part of the developer ecosystem.
Based on our record, GitHub seems to be more popular. It has been mentiond 2476 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.
"""Clones a single branch of a GitHub repository into a temporary directory for local scanning.""" Import logging Import shutil Import subprocess Import tempfile Logger = logging.getLogger(__name__) Class RepoFetchError(RuntimeError): """Raised when the target repository/branch cannot be cloned.""" Class RepoFetcher: """Shallow-clones a single branch of a repository so its tests can be scanned... - Source: dev.to / 8 days ago
# video-meta.yml Topic: > Walking through how we cut cold-start time on a Lambda-backed GraphQL API from 2.4s to under 400ms, including the two things that didn't work. Target_keyword: lambda cold start optimization Audience: backend devs who already ship serverless, not beginners Model_channels: - the three channels currently ranking for this keyword Links: repo: https://github.com/... slides:... - Source: dev.to / 9 days ago
Import struct, json, urllib.request REL = "https://github.com/{owner}/{repo}/releases/download/{tag}/" PART = ["...part1.zip.001", "...part2.zip.002", "...part3.zip.003"] SIZE = [1992294400, 1992294400, 1893639808] # from the releases API Def grab(part, start, end, out): # HTTP range fetch req = urllib.request.Request(REL + PART[part], Headers={"Range":... - Source: dev.to / 14 days ago
Is published at https://github.com/.keys so an SSH server to which you connect could do a reverse lookup. This is the reason why my ~/.ssh/config has those 2 lines at the end:- Source: Hacker News / 21 days agoHost *.
All of this assumes you can actually inspect what the agent did โ the real inputs after resolution, the real tool outputs, the real intermediate steps. That is the other half of the workflow. AgentLens captures the trace: every model and tool step, resolved inputs, raw outputs. agent-eval scores and gates the output; AgentLens gives you the unforgeable, agent-didn't-author trace data for Tier 1+2 to score against... - Source: dev.to / 22 days ago
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