Farmslot
My personal software factory for running more AI-assisted engineering work in parallel without giving up control of quality.
Why?
I started Farmslot because one agent in one terminal is not enough once the work becomes serious. I wanted a way to dispatch work into isolated worktrees, keep the runs observable, validate the result with recipes, and recover context when a session crashes or needs a second pass.
The goal is not to make a flashy agent demo. The goal is to make my own development process more repeatable: assign work, isolate it, collect evidence, review it, and decide what deserves to be merged.
What it does
- Slot-based execution: run agents in isolated worktrees with assigned ports, devices, and runtime directories.
- Recipe validation: describe what a change must prove, then collect traces, artifacts, screenshots, and logs from the run.
- Family observability: keep related attempts connected so I can compare a first run, fixes, reviews, and reruns.
- Command Center: a web surface for supervising slots, runs, artifacts, and review state.
- Mobile companion: an Expo app for checking runs and decisions when I am away from the main machine.
Current status
Farmslot is in private beta and already part of my own workflow. I am preparing the iOS companion app for TestFlight/App Store distribution, but I am not presenting it as a finished product yet. It is still very much a tool I am using, hardening, and reshaping as my process changes.
What I am trying to learn
The interesting part is not just “can an agent write code”. The question I keep coming back to is: what structure makes agentic work safe enough to scale? For me that means isolation, recipes, review loops, good defaults for Expo/native projects, and a way to inspect the actual evidence instead of trusting a summary.