I Open-Sourced My AI Cost Optimization Journey: How We Cut $800/day to Under $370/day (Without Sacrificing Output)

An honest breakdown of how we diagnosed and fixed our open-source AI infrastructure—plus a practical playbook you can apply to your own projects. The Problem: You're Probably Wasting More Than You Think Last quarter, I discovered something alarming about my open-source AI automation project. At peak usage, it was costing us roughly $800/day in API spend. Not bad for an indie project, but not sustainable either. The numbers were making me uncomfortable. At that rate, even with a reasonable user base, we'd be burning through revenue faster than growth could keep up. It was time to get serious about cost optimization. This isn't a story about finding a "magic bullet" solution or switching to some obscure model provider. Instead, it's about systematic diagnosis, making smart trade-offs, and applying proven infrastructure patterns. And yes—I'll share the actual numbers later in this post. If you're building with AI APIs, running automation workflows, or operating any AI-powered product, the