If you don't run your own LLM proxy, how do you know whats going on?

The author argues that users relying on third-party LLM providers lack meaningful visibility into their token usage and API performance, making it difficult to optimize costs and debugging. Running your own LLM proxy provides superior observability through detailed logs, multi-provider management, virtual API keys, and infrastructure control—enabling engineers to quickly diagnose issues and make informed decisions about model selection and resource allocation. The author emphasizes that owning your infrastructure and understanding your application's data flow is essential for proper stewardship of LLM operations, whether for personal learning or professional work.