In 2026, it's common to work with million-token context windows. But until recently, the cost was prohibitive. The secret to making this work is Context Caching.
How it Works
When you ask an AI to analyze your 50,000-line codebase, most of that "context" (the code) doesn't change from one query to the next. Context Caching allows the model provider (Anthropic, Google, etc.) to "store" the processed tokens of your codebase.
The Benefits
- Cost Reduction: You only pay full price for the processing once. Repeat queries using the cache are up to 90% cheaper.
- Latency Boost: Since the model doesn't have to re-read the entire context, response times are cut in half.
This development is what has enabled the "Autonomous Agent" revolution—allowing agents to live inside your codebase all day without bankrupting the company.