Having a thin python/ts orchestrator and workers that pick up tasks from the directories like events and decide whether to make deterministic calls and wait is pretty standard albeit custom way of doing things in this space where you're bottlenecked by the concurrent call your workers/agents can make.
replyThe hard thing is always keeping complexity low and being ZeroOps.
Are there any frameworks/scaffolding/harnesses or general resources on this you can share? I’d love to learn more
replyMost any ticketing system can integrate with ordinary IMAP and smtp email flow, so you can really use any agent that can "do" inbound and outbound email to talk to a self hosted ticket queue.
replyI no longer use a harness directly, instead I use Github issues/Linear to work on multiple tickets in parallel while the agents are doing work:
replySo I’ve been thinking about this problem a lot, specifically as it relates to running LLMs at home, and I’ve been using GLM-5.2 to make an SMTP/IMAP-to-LLM gateway.
replyI’ve been wondering about something similar - a system that enforces (or does the heavy lifting) of dividing a large task into smaller sub-tasks so that it’s easy to run/check/test each one independently - even on a fresh model instance if needed.
replyThis is based on the observation that the medium-sized open weight models (~20-35b) are very able to one-shot smaller discrete tasks but seem to lose their way project managing themselves through larger tasks that have multiple steps.
This is actually really smart. It would be like working with a team of humans.
replyI have a 3 Mac Studio set up and built an IDE / harness (propelcode.app) and would be interested in contributing if you’re open to collaboration
Time to make EmailGPT
replyUse the ticket system built into mininote.ink 's mcp server. Works perfect right out of the box. Also great notetaking app.
replyDocs: