Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
Summary
The arXiv preprint introduces Agentic Context Management (ACM) as a lifecycle and architecture problem for production AI agents, addressing how context memory and costs are managed. It outlines five primitives for ACM and argues that proper context compaction yields linear token costs with preserved fidelity, plus a reference implementation Maximem Synap and future benchmarking areas.