No single GPT needs to do everything.
A network of small, specialized assistants often works better.
Assign each GPT a focused role — planning, outlining, analysis, or refinement.
This keeps instructions light, behavior sharp, and outputs consistent.
You move between assistants the same way you would move between tools in your workflow.
Smaller GPTs are easier to test, calibrate, and improve.
They also create modularity; you can replace or upgrade one without disrupting the others.
A simple network of assistants gives you flexibility without added complexity.