
7/15/2026
What this post added
This post defines and elaborates on the concept of AI Total Cost of Ownership (TCO) for enterprises. It breaks down AI costs beyond token pricing to include infrastructure, system complexity, and operational expenses. It introduces the idea of owning vs. renting AI infrastructure and provides data-driven comparisons of the cost-effectiveness of each approach, particularly highlighting the benefits of owned hardware for high-volume inference. The post also touches upon model efficiency techniques like MoE and quantization as cost-reduction strategies.