Dhravya Shah explains Supermemory's internal evaluation of different agent memory architectures.
Opinion
Shah: Claude Code avoids indexing because vendors profit from high token usage
“They could index the code and cursor does, but plot code does not. And I believe this is also because they are not incentivized to utilize less tokens by the end user, because they're just offsetting the cost of indexing, et cetera, to tokens and time that the…”
Insight
Shah: OpenClaw memory fails because LLMs frequently skip search tool calls
“The way OpenClaw has with QMD or with whatever memory plugin you use, it inherently relies on tools to search through these memory.md files that it prepares. So, you know, like, what did I decide about the API? Then agent will decide to search, and sometimes i…”
Assertion Supported
Shah: OpenClaw's 15-message replay fails prompt caching and costs 10x more
“The way OpenClaw does it is it essentially sends back the last 15 messages in the conversation and it essentially uses that back and forth. And I mean, the approach itself is not ideal because you will, like, you are not doing any, like, you're not utilizing a…”
Opinion
Shah: Most vector databases become too slow or expensive at scale
“So, so, better databases, like, at that time, and even now, except a few, like, TurboPuffer and Chroma, Were not really scalable for the scale I was getting to where they were either getting too slow or too expensive to run.”
Opinion
Shah: Triplet-Based Knowledge Graphs Degrade AI Memory Performance
“And we think that triplets actually Lead to worse performance because you have to traverse them a lot to get to any information.”
Opinion
Shah: LongMemEval is good but reward-hacks memory extraction volume
“LongMemival is a very good benchmark because it calculates, it tests for the right things. It tests for the right things, the data set is great, everything is really good in LongMemival, except for the fact that you can win LongMemival by remembering as many t…”