Agentic Context Management Argues Naive Context Accumulation Costs Grow Quadratically — and Crude Summarization Buys Linear Cost at an Accuracy Cliff

arXiv 2607.21503·medium signal

Gaurav Dadhich reframes agent memory from a storage-and-retrieval problem into a lifecycle-and-architecture discipline with five primitives — architecting, ingesting, scoping, anticipating, and compacting & consolidation — operating across an organizational scope hierarchy rather than a single user. The economic argument is the sharpest part: naive accumulation grows token cost quadratically in conversation length, crude summarization trades that for linear cost but hits an accuracy cliff, and only validated compaction achieves linear cost with preserved fidelity. The reference implementation, Maximem Synap, reports 92% on LongMemEval and 93.2% on LoCoMo, and the paper calls out latency, token efficiency, and context-rot resistance as dimensions no current benchmark captures.