alt Hacker NewsThere are a variety of possible memory mechanisms including simple things recording a transcript (as a chatbot does) or having the LLM update markdown docs in a repo. So having memory isn't interesting. Instead, my question is: what does Letta's memory look like? Memory is a data structure. How is it structured and why is that good?
I'd be interested in hearing about how this approach compares with Beads [1].
Beads looks cool! I haven't tried it, but as far as I can tell, it's more of a "linear for agents" (memory as a tool), as opposed to baking long-term memory into the harness itself. In many ways, CLAUDE.md is a weak form of "baking memory into the harness", since AFAIK on bootup of `claude`, the CLAUDE.md gets "absorbed" and pinned in the system prompt.
Letta's memory system is designed off the MemGPT reference architecture, which is intentionally very simple - break the system prompt up into "memory blocks" (all pinned to the context window, since they are injected in system, which are modifiable via memory tools (the original MemGPT paper is still a good reference for what this looks like at a high level: https://research.memgpt.ai/). So it's more like a "living CLAUDE.md" that follows your agent around wherever it's deployed - ofc, it's also interoperable with CLAUDE.md. For example, when you boot up Letta Code and run `/init`, it will scan for AGENTS.md/CLAUDE.md, and will ingest the files into its memory blocks.
LMK if you have any other questions about how it works happy to explain more