Each of these has a file it listens to in ~/tmp/<name>.io and whenever one needs something from the other, they message each other via that file. Tasks can bounce back and forth as issues are resolved and tested. At the same time, I keep each busy with a list of tasks
I can fairly easily run out of my $200/month subs every week, if I let Fable be the default model. With Opus it’s less likely. If and when I do, I just have an alias ‘claude.ds’ which fires up Deepseek instead, and burns through far less money, though I don’t think it’s as good at solving problems, just MHO.
Why isn't this just one coherent agent loop with subtools/agents as appropriate? If these tasks are related in some way, having a single context would probably make it go much better.
The freewheeling messaging part is where the token bloat is coming from. I suspect that for some of us this is actually the point. I think it's a mostly form of entertainment to do things this way. The next logical step from Factorio gameplay.
Parallel agents remind me a lot about multi core compute. It's incredibly easy to take a single core product and make it run much worse across a lot of cores.
I also find that it's easy to spend like that, but also easy not to with little impact on productivity. At the current moment I'm stuck with rider + copilot (not ideal), but e.g. using GPT 6.1 luna is really, really cheap, and lots of tasks are quickly and decently dealt with even at lower reasoning levels, (added bonus of having low latency). And that model is so cheap, I can't see a hitting 1500$ at api prices realistically - not even close. But it also depends on the harness and codebase.
I don't have the mental capacity to do a lot of context switching between active work streams, so I'm not doing stuff like leaving a big agent workflow running while doing other things.
All through claude code.