A new metric, known as the expenditure horizon, has been introduced to measure the cost-effectiveness of artificial intelligence agents. The metric assigns a dollar value to the point at which AI agents become more expensive than humans for solving problems. Initial results from the NanoGPT speedrun have been disappointing, and the metric has limitations. Additionally, the emergence of newer AI model generations may alter the current assessment. The development of this metric aims to provide a more precise understanding of AI's economic viability. This metric matters as it could influence the adoption and deployment of AI in various industries.