Google Agentic Architect - Subconcept 3.3: Context Window Optimization & Cost Controls

Address the token economics and operational latency of long-running agent sessions. Detail three key optimizations: 1) Sliding Window Pruning, explaining how to maintain a rolling history of only the last K=6 to 10 active turns while archiving older interactions; 2) Asynchronous Map-Reduce Conversation Summarization, where a fast model like gemini-1.5-flash or gemini-2.5-flash compresses past turns into a high-level context block; and 3) Gemini Context Caching, outlining how caching static system instructions and tool schemas exceeding 32k tokens reduces execution latencies by up to 80% and API costs by up to 75%.