Original Summary

Since May I’ve been building Snotra, an open-source desktop AI agent. You open a folder, the chat sits beside it, and the agent reads, writes and runs things in there, but asks before it changes anything. Any model, cloud or local (Ollama, LM Studio, llama.cpp). No account, no telemetry, Apache 2.0. The numbers, as of today: 604 commits, 60 releases, ~81k lines of JS, 305 test files 4 stars ~100 downloads, and I can’t tell how many of those are people, because the app asks GitHub for updates and I collect no telemetry Why I’m not upset (mostly) It started as an experiment: I wanted to see what actually travels between a language model and the program driving it. Somewhere along the way, building it became the fun part. Try a variant, add one more capability, see what a model does with it. There’s nothing to sell: no paid tier, no sign-up, no waitlist. So four stars stings a little, but it isn’t a failed business. The AI part, since someone will ask About five in six commits carry an AI co-author line, mostly Claude. My part shifted to writing issues (500 and counting), deciding what gets built and what doesn’t, and reading every diff before it merges. The code turned out to be the cheap part. What 60 releases without users taught me Shipping and being found are two separate projects. I literally keep them in two separate repos. Without telemetry, a star is the only way I learn someone liked it, and an issue the only way I learn what broke. A release count measures how much I enjoy building. It says nothing about whether anyone needs the thing. For those of you who got past the first handful of stars: what made the difference? A specific post, a niche community, or just time? Repo: https://github.com/kkrafft1999/snotra Site: https://snotra-ai.dev   submitted by   /u/DraftForsaken39 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/11 00:54:42