Caching Strategy: The Optimization That Creates Its Own Category of Bug Caching stores the result of an expensive computation or query so subsequent requests can reuse it. Caching is the practice of storing the result of an expensive operation so future identical requests can reuse it instead of recomputing. Phil Karlton's line — 'there are only two hard things in computer science: cache invalidation and naming things' — endures because caching adds a shadow layer of state that must be kept coherent with the source of truth. Every cache buys latency and throughput at the cost of complexity, staleness risk, and a new category of bug where the code is correct but the cached data is not. Read the full guide on Startup Fundraising · Find investors · Browse the Library Related guides Beachhead Strategy: Winning One Segment Before Expanding to Ten Brand Strategy for B2B Startups: The Asset Most Founders Underinvest In Channel Strategy: Direct, Partner, and Marketplace Distribution Content Strategy for B2B Startups: The Discipline Behind the Blog CPG M&A Strategy Data Warehouse Strategy: The Investment That Pays for Itself the Second Time Someone Asks 'How Many Customers…?' Exit Strategy for Startup Founders Free Trial vs Freemium: Choosing the Right Model and Making It Convert Webinars in 2026: Why Most Fail and What the 10% That Work Do Differently Wedge Strategy for Startups
