---
title: "What We Learned Evaluating Agent Memory:The Results (Part 2)"
url: https://daily.dev/posts/what-we-learned-evaluating-agent-memory-the-results-part-2--cfjxen3ox
source_url: https://www.couchbase.com/blog/what-we-learned-evaluating-agent-memorythe-results-part-2
type: article
source: "Couchbase"
published: 2026-07-29T16:04:07.534Z
updated: 2026-07-29T16:04:33.624Z
tags: ["rag", "vector-search", "couchbase"]
reading_time: 10
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# What We Learned Evaluating Agent Memory:The Results (Part 2)

**[Couchbase](https://daily.dev/sources/couchbase)** · 10 min read · 0 upvotes · 0 comments

## Summary

A detailed experimental evaluation of Couchbase Agent Memory across three benchmarks (LME-S, LME-M, LoCoMo) reveals several non-obvious findings. Raw conversation messages outperform LLM-generated summaries overall, especially for questions requiring exact entity matching. Optimal retrieval depth (k) varies by haystack scale — k=10 for small, k=20 for large — and more context beyond the optimum degrades performance. Temporal reasoning is the weakest category but improves ~7x by simply prepending session dates to stored memories at ingestion time. BM25 reranking with large initial pools hurts performance, while hybrid search improves temporal recall at the cost of multi-session precision. The key takeaway: agent memory has a distinct design space from document RAG, no single configuration is universally optimal, and systems tuned on small benchmarks may be misconfigured at production scale.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.couchbase.com/blog/what-we-learned-evaluating-agent-memorythe-results-part-2>

## Similar posts on daily.dev

- [What We Learned Evaluating Agent Memory:The Setup \(Part 1\)](https://daily.dev/posts/what-we-learned-evaluating-agent-memory-the-setup-part-1--tyaycnpsz) · Couchbase · 1 upvotes · 1 comments
- [Why Agent Memory Should Store Facts, Not Conversations](https://daily.dev/posts/why-agent-memory-should-store-facts-not-conversations-ee6iupetr) · Medium · 1 upvotes · 0 comments

---

Tags: [#rag](https://daily.dev/tags/rag), [#vector-search](https://daily.dev/tags/vector-search), [#couchbase](https://daily.dev/tags/couchbase)

[View this post on daily.dev](https://daily.dev/posts/what-we-learned-evaluating-agent-memory-the-results-part-2--cfjxen3ox)
