One surprising insight in optimizing token usage is that many overlook the power of dynamic prompt engineering. By pre-processing input data to tailor prompts specifically for each agent's task, you can cut token usage significantly. This approach involves creating a modular prompt framework that adapts to the agent's context, reducing verbosity without losing essential information. I wrote more about this here: enterprise.colaberry.ai/i/oc-hashnode-0672928f