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title: "Agent memory - New Runtime"
description: "Evidence on agent memory as a write loop: what should persist, who can correct it, and how it changes future work."
answer: ["Agent memory is not only retrieval; it is a governed write loop that decides what survives a task.","Useful memory needs correction-time updates, provenance, decay, and behavioral evaluation.","The failure mode is treating memory as a passive store while the actual system behavior drifts."]
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---

# Agent memory - New Runtime

Evidence on agent memory as a write loop: what should persist, who can correct it, and how it changes future work.

## Short Answer

- Agent memory is not only retrieval; it is a governed write loop that decides what survives a task.
- Useful memory needs correction-time updates, provenance, decay, and behavioral evaluation.
- The failure mode is treating memory as a passive store while the actual system behavior drifts.

## Patterns

- [Company memory needs write and correction loops](https://newruntime.com/patterns/company-memory-needs-write-loops/): Company memory becomes useful when real work continuously updates a governed knowledge layer, not when an agent merely searches a larger document pile.

## Field Notes

- [Cognee Packages Agent Memory as a Self-Hosted Knowledge Graph](https://newruntime.com/posts/cognee-agent-memory-platform/): Cognee matters less as another memory SDK and more as an attempt to package persistent agent memory through ingestion, graph/vector search, ontology, and self-hosting.

## Recent Raw Signals

- 2026-07-06: [Agent memory is being evaluated as system behavior](https://newruntime.com/signals/agent-memory-evaluated-as-system-behavior/)
- 2026-07-03: [Codebase Memory Combines Search with a Repository Map](https://newruntime.com/signals/codebase-memory-combines-search-with-a-repository-map/)
- 2026-07-02: [Agent Memory Needs Its Own Review Loop](https://newruntime.com/signals/agent-memory-needs-its-own-review-loop/)
- 2026-07-01: [Deep Agents combines plans, files, memory, and subagents](https://newruntime.com/signals/deep-agents-plan-files-memory-subagents/)
- 2026-06-24: [DoorDash makes memory a versioned personalization layer](https://newruntime.com/signals/doordash-memory-is-versioned-personalization-layer/)
- 2026-05-24: [OpenHuman Builds a Personal Harness Around Local Memory](https://newruntime.com/signals/openhuman-builds-a-personal-harness-around-local-memory/)
- 2026-05-19: [AgentMemory Shares State Across Codex, Claude Code, and Cursor](https://newruntime.com/signals/agentmemory-shares-state-across-codex-claude-code-and-cursor/)
- 2026-05-07: [OpenAI Shows Memory Compaction for Long-Running Agents](https://newruntime.com/signals/openai-shows-memory-compaction-for-long-running-agents/)
- 2026-05-06: [CocoIndex Keeps Agent Context Fresh Without Full Reindexing](https://newruntime.com/signals/cocoindex-keeps-agent-context-fresh-without-full-reindexing/)

## Public Sources

- https://aclanthology.org/2024.acl-long.747
- https://careersatdoordash.com/blog/doordash-unified-consumer-memory-for-personalization-at-scale
- https://developers.openai.com/cookbook/examples/agents_sdk/building_reliable_agents_memory_compaction
- https://github.com/AI-Builder-Club/skills
- https://github.com/cocoindex-io/cocoindex
- https://github.com/langchain-ai/deepagents
- https://github.com/langchain-ai/openwiki
- https://github.com/openai/openai-cookbook/blob/main/examples/agents_sdk/building_reliable_agents_memory_compaction.ipynb
- https://github.com/OpenDataBox/MemoryData
- https://github.com/rohitg00/agentmemory
- https://github.com/tinyhumansai/openhuman
- https://github.com/topoteretes/cognee