Cost Reduction

Five Ways to Cut the Cost of AI Coding Agents | Model Switching, Open-Source Agents, Open Weights, Domestic Serverless Inference, On-Prem GPUs, and the Gateway That Keeps Data In-Country

Coding agents such as Claude Code, Codex and Grok Build have grown heavy, and token bills are becoming a board-level topic. Using only what official documentation confirms, this piece lays out five ways to bring the cost down: switching the model an agent talks to, open-source agents such as OpenCode and Hermes Agent, open-weight models from China, NVIDIA, Google and others, domestic serverless inference such as Sakura's AI Engine, and on-prem operation on hardware such as DGX Spark or Mac Studio. It explains the pitfalls of each and, for newcomers, the idea of an AI gateway that cuts cost while keeping data in-country.