Actually more AI agents do the work faster and cheaper.
I use such orchestration for those 2 reasons. One, a supervisor model like Opus 5.5 (or fable before they lobotomised it) limited to 200k of context and told to keep it's progress updated in a text file is smart enough to understand the whole task.
It farms smaller sub tasks to a fleet of 7 Qwen3.8-Flash-Next agents. Not only it uses up 10% of the tokens opus would use those 7 agents run at an aggregate rate of 200tok/s. While opus would run at few dozen at most.
The Qwen in this example runs locally. If you don't mind sending your code to China you can spin a bunch of DeepSeek Flash agents and each will run at ~150-200t/s. Then your task gets done way, way faster
I use such orchestration for those 2 reasons. One, a supervisor model like Opus 5.5 (or fable before they lobotomised it) limited to 200k of context and told to keep it's progress updated in a text file is smart enough to understand the whole task.
It farms smaller sub tasks to a fleet of 7 Qwen3.8-Flash-Next agents. Not only it uses up 10% of the tokens opus would use those 7 agents run at an aggregate rate of 200tok/s. While opus would run at few dozen at most.
The Qwen in this example runs locally. If you don't mind sending your code to China you can spin a bunch of DeepSeek Flash agents and each will run at ~150-200t/s. Then your task gets done way, way faster