Caching (LRU Cache)

A computing strategy that stores frequently or recently accessed data closer to where it's needed, dramatically reducing retrieval time at the cost of storage space. LRU (Least Recently Used) evicts the oldest unused data when the cache is full. The principle extends beyond computing: your desk is a cache for frequently used items; your mental models are a cache for frequently used analytical frameworks; organizational routines are cached decision procedures that avoid re-deliberating every choice. Effective caching is the difference between fast and slow systems.

When to use it

When the same information or decisions are being retrieved or re-made repeatedly; when system speed is bottlenecked by retrieval time; when designing workflows, information architectures, or decision processes; when personal or organizational productivity is limited by access time to frequently needed resources.

How it can help

Identify where retrieval time is a bottleneck in your workflows and build caches. Keep your most-used tools, references, and templates immediately accessible. Build decision templates for recurring situations (cached decision procedures) so you don't re-analyze from scratch each time. For organizations: standard operating procedures ARE caches—pre-computed solutions for common situations. The LRU principle for personal productivity: the things you use most should be fastest to access. Regularly evict what you no longer use to keep your cache relevant.