How I dropped my OpenClaw cost of ownership 17x with OpenRouter

Running autonomous AI agents like OpenClaw can be costly when relying on expensive models such as Claude Opus 4.6 for every task, leading to high monthly expenses. OpenClaw, an open-source AI agent, was initially set to use Opus for all interactions, which proved to be an inefficient use of resources, especially for simple tasks that didn't require high-level reasoning. By adopting a tiered model strategy with OpenRouter, the author optimized costs by routing different types of requests to appropriate models: MiniMax for general chat, Opus for complex reasoning, and Claude Sonnet 4.6 for implementation tasks. This approach resulted in a dramatic 17x reduction in total costs without compromising the quality of work, demonstrating the importance of model routing in managing AI operation expenses effectively.