AI inference is rapidly moving out of the data center and onto local machines. With hardware like the upcoming Mac Studio M5 Ultra, it’s already possible to run top open models locally at performance levels approaching systems like ChatGPT. At the same time, companies like SK Hynix and Micron Technology are pushing memory bandwidth forward, making edge inference increasingly practical. But the software layer hasn’t caught up yet. We have great building blocks (e.g., OpenClaw), but they don’t yet provide the reliability guarantees you’d expect from production systems like Temporal Technologies—things like durable execution, failure recovery, and long-running workflow management. So I built MirrorNeuron: https://www.mirrorneuron.io GitHub: https://github.com/MirrorNeuronLab MirrorNeuron is an open-source runtime for AI agents that need to run continuously and reliably on edge or local environments. The focus is simple: long-running, stateful agent workflows fault tolerance and recovery b...