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thefunnyman • today at 1:54 AM • 1 reply • view on HN

$DAY_JOB gives me GitHub Copilot with generous limits so I use GitHub Copilot CLI. We're a Microsoft shop so that dictates some choices too.

My workflow is a windows terminal app with multiple sessions running under wsl2 in each pane since LLMs seem to do better with bash than PowerShell. I don't trust these things much so I've got a careful list of read only tool calls and filesystem sandboxing set up so it can do some useful stuff like read my task board and publish draft PRs without a ton of overbearing permissions prompts.

I usually chat with that for a bit on a task until it's plan sounds good then I have it spin up a Docker Sandbox microvm under Windows so it can safely run yolo mode and make all it's changes. When it's ready I carefully review and iterate on the result until it's ready to publish the PR.

Bit kludgy but strikes a balance of safety and multitasking I'm comfortable with. IME most folks don't think much about isolation so curious to hear if anyone else has a similarly isolated but better workflow. I'd like to try OpenShell instead of docker sbx but it lacks microvm support for windows and I don't want another layer of nested virtualization since my windows machine itself is a cloud VM.

Work also gives me access to GHCP for personal use so I use it for side projects too. Idk what I'd use if I had to pay out of pocket, probably something a cheap Claude plan. For noncoding personal use I mostly just use free tier Gemini. If this stuff ever slows down I'll invest in some GPU nodes for my homelab and run local models.


Replies

thefunnyman • today at 2:06 AM

Our token budget is also high so honestly I don't plan much. Mostly just throw work item and as much related context I'm aware of at whatever is the latest decent model (opus for a while and lately gpt sol) and let it do its thing. If I were more budget constrained I'd plan more up front and delegate bits to cheaper subagents I suppose.