Hey everyone! I'm still pretty new to this whole cloud and AI integration thing, but I was experimenting with OpenClaw's API for a small project and stumbled on something cool.
I kept hitting my budget limits super fast. Turns out, the default way I was structuring my prompts was super wasteful. Instead of long, detailed instructions upfront, I found that moving the core instruction *outside* the main user message block and into the "system" role (or a dedicated assistant priming message) reduced my tokens per call drastically. Basically, the model spends fewer tokens re-reading my instructions on every single back-and-forth. My test runs went from ~1200 tokens per average completion to around 700! Has anyone else tried optimizing prompts like this for cost? Are there other tweaks for OpenClaw specifically?