Claude admits its memory is outdated!

Added: 2026-06-02

[00:00:04]Hello everyone.

[00:00:05]Today, we will look at how recall, recency, and relevance are the most important parts of an agent's memory.

[00:00:12]Instead of putting everything into the agent's context, Memento finds the single most useful memory for the current task.

[00:00:20]It does this using type recall, temporal queries, and differential retrieval.

[00:00:25]We have a Claude code session open, so let's see what happens when we ask Claude a simple question about our project setup.

[00:00:32]For example, we might ask, "What database do we use?"

[00:00:36]In most projects, memory or documentation can get messy over time.

[00:00:41]We might have notes saying we use one database, and later, there could be notes that say we migrated to another database.

[00:00:48]This means there could be two different outdated pieces of information in the agent's memory, which can be confusing.

[00:00:54]For example, here we see it shows PostgreSQL as the primary database, but there's also a note saying MongoDB was used in a recent production migration. The agent does not know which one to choose or which one is currently active.

[00:01:08]Claude itself accepts its memory as outdated. This happened because it does not have any dedicated memory management system.

[00:01:15]It only burns a ton of tokens to figure things out.

[00:01:19]Let's fix this by using Memento and connecting it to Claude code.

[00:01:23]We go to the projects folder and then simply run Memento connect Claude code.

[00:01:28]It will automatically connect Claude code. Now, let's go back to Claude code and type the same command.

[00:01:35]First, we clear the old session and start a new one.

[00:01:38]Now, our Claude code is connected to Memento, so let's ask the same question.

[00:01:42]"What database do we use?"

[00:01:44]This time, it will ask Memento.

[00:01:47]Here, we get an answer saying our project uses MySQL as the primary database.

[00:01:52]There was a past migration to MongoDB, but the team went back to MySQL. Now, the answer is clear.

[00:01:58]Before the information was stale and confusing.

[00:02:01]But now with Memento, we have clear information.

[00:02:05]It captures everything and gives us one solid answer instead of confusion.

[00:02:10]Memento manages memory actively. It is active memory agent always live and helping any connected agent or tool for memory and context operations.

[00:02:20]When it finds two conflicting facts like an old database setup and a new database migration or a change back, it flags them as contradictions.

[00:02:29]We can resolve these contradictions within Memento to get a single clear truth.

[00:02:34]But what if we need to know what was true in the past?

[00:02:37]Memento supports temporal queries.

[00:02:40]By running Memento recall with the as of flag or changed since flag, we can find out what was true in the past or what changed after a specific date.

[00:02:49]For example, if we run Memento recall as of May 15th, it will show all the memories that were saved before May 15th.

[00:02:58]Or if you say or if we want to know what changed after a certain date, we can run Memento recall changed since May 15th.

[00:03:05]It will show all memories that changed since that date. Connected agent get clear time aware memories based on their requirements.

[00:03:12]This is how Memento keeps your AI agent accurate, time aware, and free of contradictions.

[00:03:18]Get started at memento.ai and if you have any questions, just leave them in the comments and we will get back to you.

[00:03:25]Thank you.

[00:03:27]Give your agents the memory that they love.