How important is human-agent experience (HAX) in the AI space?

Memory (or context) is a very interesting problem in AI, but not for the reason most people think.

This is the first layer that needs to be EQUALLY READABLE BY MACHINES AND HUMANS (opinions are my own).

I have done an extensive analysis of the current products in the space, some of which are heavily funded like Mem0 or supermemory.

Current focus areas include making retrievals faster, hitting benchmarks, expanding the product surface (all valid problems).

But they're all missing the human-agent interaction part.

Right now, memory works like this: you give an context engine your memories as a dump and then it does its thing and start providing your agents the required context.

But keep doing it for a while (in any product of your choice) and then slowly it becomes a junk drawer where you know you put something but where was it, why did you add it, who changed it, poof. Good luck at that point.

This is one of the areas I'm obsessed with. How do we make context engineering as simple as a perfectly organized notion, and still ridiculously easy for agents to retrieve as well.

What I keep wrestling with in my mind these days: Imagine you are an AI-native individual with 100s of documents and dozens of ongoing clients, is a knowledge graph really the right abstraction?

What "context abstraction" would you want if you are working with agents day-in day-out?