One of the clearest proven use cases for AI Optimizer is OpenAI API usage from the command line. If you repeat prompts, test requests, run scripts, or iterate locally, a caching proxy can help reduce duplicate spend without forcing you into a major rewrite.
Command-line usage naturally creates repeated requests during testing, debugging, iteration, and prompt refinement. AI Optimizer gives those workflows one local path through a caching proxy.
You usually do not need to redesign your workflow. The practical change is routing your OpenAI base URL through the local optimizer endpoint.
Developers often ask the same thing slightly differently, re-run checks, and test the same logic over and over. That is exactly where repeated request waste shows up.
This is one of the strongest current positions for the product right now, alongside OpenClaw through the OpenAI API.