Letta now provides Anthropic's `memory` tool, enabling agents to dynamically manage their own memory architecture.
The memory tool is something I have wanted since before I started working at Letta, but never had the bandwidth to implement. Our researcher Kevin Lin ended up hacking it together in an evening, and it works swimmingly. But what does it enable?
Currently, Letta agents have a fixed memory architecture. A memory architecture is a set of memory blocks to track various types of information, such as communication guidelines, information about a user, company policies, how to use various tools, etc. Memory architecture can allow the agent to learn about nearly any type of information and persist it through its lifespan.
However, agents have not been able to modify this architecture themselves. They could modify what was INSIDE the blocks, such as including a note about how I like dogs when I mention it.
But the agent could not add a new block to track information that was unanticipated. For example, if the agent recognizes that it is struggling with understanding how to use tools, it either had to write tool use guidelines to some other block ill-suited for that purpose, or simply lose the information.
With the memory tool, the agent can decide to add a new block to accomodate this information. You can either ask it to add the block if you notice it struggling, or it may even choose to add the block itself.
The memory tool also allows "peeking" on blocks stored in something like a filesystem, such as /notes/letta to track the agent's notes on Letta. The agent can look at what is inside this memory without having to load it permanently into its context, which helps memory blocks resemble a filesystem.
I am extraordinarily proud of this tool and how quickly it came together. My sense is that this tool is one of the final building blocks needed to make Letta agents genuinely self-improving -- their "shape" is now under their own control, and they can now adapt much more readily to changing environments.
cpfiffer•4mo ago
Letta now provides Anthropic's `memory` tool, enabling agents to dynamically manage their own memory architecture.
The memory tool is something I have wanted since before I started working at Letta, but never had the bandwidth to implement. Our researcher Kevin Lin ended up hacking it together in an evening, and it works swimmingly. But what does it enable?
Currently, Letta agents have a fixed memory architecture. A memory architecture is a set of memory blocks to track various types of information, such as communication guidelines, information about a user, company policies, how to use various tools, etc. Memory architecture can allow the agent to learn about nearly any type of information and persist it through its lifespan.
However, agents have not been able to modify this architecture themselves. They could modify what was INSIDE the blocks, such as including a note about how I like dogs when I mention it.
But the agent could not add a new block to track information that was unanticipated. For example, if the agent recognizes that it is struggling with understanding how to use tools, it either had to write tool use guidelines to some other block ill-suited for that purpose, or simply lose the information.
With the memory tool, the agent can decide to add a new block to accomodate this information. You can either ask it to add the block if you notice it struggling, or it may even choose to add the block itself.
The memory tool also allows "peeking" on blocks stored in something like a filesystem, such as /notes/letta to track the agent's notes on Letta. The agent can look at what is inside this memory without having to load it permanently into its context, which helps memory blocks resemble a filesystem.
I am extraordinarily proud of this tool and how quickly it came together. My sense is that this tool is one of the final building blocks needed to make Letta agents genuinely self-improving -- their "shape" is now under their own control, and they can now adapt much more readily to changing environments.
Very, very cool stuff.