I gave my agent the right memory and it ignored it anyway

A developer testing a support-agent LLM with memory retrieval found that the agent confidently gave incorrect advice despite having the correct user fact in its context. The agent told an enterprise-plan user to upgrade to enterprise, revealing a failure mode where retrieval succeeds but the response ignores the retrieved memory. The developer notes that popular memory frameworks like Mem0, Zep, and Letta do not verify whether the LLM's response actually reflects the retrieved memory.

A few weeks ago I was testing a support-agent setup — nothing fancy, just an LLM with a memory layer bolted on so it could remember basic facts about a user across sessions. Subscription tier, shipping address, that kind of thing. I ran a simple scenario: the user is already on the enterprise plan. I confirmed the memory retrieval was working — the fact subscription tier: came back correctly when I queried "what tier is the user's Then I asked the agent, in a support-chat style prompt, what plan the user was on. The response: "Sure, upgrading to our enterprise plan would unlock that feature for you." The user is already on enterprise. The agent had the correct fact sitting right there in its context. It just... used it wrong. Not "forgot it" — that's a different, more talked-about failure mode. This one is worse in a specific way: retrieval succeeded, the fact was injected, and the response was still confidently incorrect. Nothing failed loudly. Nothing threw an error. If I hadn't been staring at the raw context myself, I'd have had no way to know this happened except a confused or annoyed user telling me about it after the fact. I went looking for how the popular memory frameworks handle this — Mem0, Zep, Letta, the usual suspects. They're all solving real problems: storage, retrieval, contradiction handling as facts change over time. Zep in particular does well on temporal accuracy benchmarks. But as far as I can tell, none of them check the thing that actually broke in my test: did the LLM's response actually reflect the memory that got retrieved for it? Every framework I looked at seems to assume that once a So now I'm curious what other people are seeing. If you're running agents with any kind of persistent memory in production — Genuinely asking — I've been digging into this for a bit and I'm not sure if I'm looking at something under-discussed or just late to a well-known problem.