How to Save Tokens: Practical Strategies for Efficient AI Usage
This article explores practical engineering strategies to reduce token usage in AI systems. It focuses on system design, data structuring, time normalization, context management, and architectural optimization rather than prompt tricks. From using Unix timestamps for efficient time representation to building token-aware AI infrastructures, the guide provides real-world methods to build scalable, cost-efficient, and stable AI services for long-running production environments.
