I'm juggling multiple claude ultra subs, multiple codex $500 a month subs, antigravity for argon, plus API rate deepseek 4.1 flash, mercury 3, and abliterated large v2 for red teaming.

I work across multiple models and harnesses using a really simple redis-backed message bus called "nova-bus": https://github.com/mas-bandwidth/nova-tools (open source).

With just this message bus, I can coordinate AIs to work together at a normal pace (worktrees, subtasks etc...), but past a certain point the AIs can't keep up and I need to use a sprint card system I developed to coordinate work.

With this sprint system I'm able to work 200 cards wide (each card is around 30-60 minutes of LLM work in a session) across a fleet of 20 machines linked together with tailscale and ssh.

Full system is here: https://github.com/mas-bandwidth/nova-sprint (open source)

It's been very effective at getting high throughput, but afterwards I find that the resulting code can be a bit of a pastiche from different models working in isolation, thus a good pass over working directly with models to clean up and harden the code is necessary.

I find that using nova-bus to coordinate multiple model/harness review of codebase in very effective at increasing code quality. Each model sees things the others don't.