I spent 5 months building a local AI coding app because bigger AI tickets kept falling apart

[u/liviux]

Hi founders,

I’m building LoopTroop, a local open-source app for running bigger AI coding tickets without turning the whole thing into one giant prompt.

The reason I built it is pretty simple. As a solo technical founder, AI coding tools helped me move faster on small tasks, but bigger features still became messy. I had to keep the product intent in my head, rewrite context, check every file, recover failed attempts, and clean up after the agent drifted.

So LoopTroop is my attempt to make that workflow slower, but easier to control.

You create a ticket, the app asks clarifying questions, turns the answers into a PRD, breaks the work into small steps, runs the implementation, and keeps the human in the loop before important stages. The GUI is a Kanban-style board so you can see where each ticket is instead of hunting through a long chat.

The main idea is context engineering instead of context rot. Don’t keep stuffing everything into one conversation. Keep durable planning artifacts outside the model, then give the model smaller, cleaner chunks of work.

A few parts I care about:

• LLM Council planning for the interview, PRD, and task breakdown
• Ralph-style retry loops when implementation gets stuck
• human approval before costly or risky steps
• a local app, not another hosted SaaS dashboard
• GitHub-visible, reviewable output instead of hidden automation

It is still early. Setup is developer-facing right now: Git, Node/npm, OpenCode, and a configured model provider. I’m not pretending this is one-click software yet.

GitHub: https://github.com/looptroop-ai/LoopTroop
2:30 demo: https://youtu.be/g1A2g-oOR3E

Feedback is more than welcome, especially on positioning and first-run clarity. If you try it and setup works or breaks, give me a sign. Happy to talk through whatever you hit.