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Comment by CPLX | Hacker News Reader

I absolutely love this concept! It's like the thing that I've been looking for my whole life. Well, at least since I've been using Claude Code, which is this year.

I'm sold.

With that said, I can't think of a way that this would work. How does this work? I took a very quick glance, and it's not obvious at first glance.

The whole problem is, the AI is short on context, it has limited memory. Of course, you can store lots of memory elsewhere, but how do you solve the problem of having the AI not know what's in the memory as it goes from step to step? How does it sort of find the relevant memory at the time that that relevance is most active?

Could you just walk through the sort of conceptual mechanism of action of this thing?

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Appreciate it - yeah, you're right, models don't work well when you just give it a giant dump of memory. We store memories in a small DB - think key/value pair with embeddings Every time you ask Claude something, the skill:

1. Embeds the current request.

2. Runs a semantic + timestamp-weighted search over your past sessions. Returns only the top N items that look relevant to this request.

3. Those get injected into the prompt as context (like extra system/user messages), so Claude sees just enough to stay oriented without blowing context limits.

Think of it like: Attention over your historical work, more so than brute force recall. Context on demand basically giving you an infinite context window. Bookmark + semantic grep + temporal rank. It doesn’t “know everything all the time.” It just knows how to ask its own past: “What from memory might matter for this?”

When you try it, I’d love to hear where the mechanism breaks for you.

It looks to me like the skill sets up a connection to their MCP server at api.ensue-network.ai during Claude session start via https://github.com/mutable-state-inc/ensue-skill/blob/main/s...

Then Claude uses the MCP tools according to the SKILL definition: https://github.com/mutable-state-inc/ensue-skill/blob/main/s...

yeah so you can run it in automatic mode, or read only mode. In automatic mode it hooks onto the conversation and tool calls so you get the entire conversation stored. If you dont want to get super deep, then read only is safe and only stores what you ask. You could ask it things like "why is my reasoning dumb" by recalling passed conversations, or even give it the claude tool call sequence and ask "how can claude be smarter about next time".

I think of it like a file tree with proper namespacing and keep abstract concepts in separate directories. so like my food preferences will be in like /preferences/sandos. or you can even do things like /system-design preferences and then load them into a relevant conversation for next time.

Total speculation:

Text Index of past conversations, using prompt-like summaries.

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