Memory management
AssessTechniques
Methods for storing, tiering, and retrieving information for stateful AI agents.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 5InfoQ·6/10/2026researchContext Engineering and Memory Management for AI at Scale
Adi Polak outlines how AI systems can move from stateless prompting to state-aware agents with richer context and persistent memory. She highlights Apache Kafka, Flink, and MCP as building blocks for real-time processing, memory tiering, and tool orchestration while addressing token limits, latency, and cost.