What do you hate about AI memory systems today!
Everyone went crazy in 2025 after AI Memory. There are atleast a dozen launches in the space on product hunt from june-december, but the problem seems far from solved.
Are you using any of the current memory systems (platform specific or interoperable ones, doesn't matter).
What do you still hate in these systems? is it context repetition? is it hallucinations? is it inability to move between systems with your memory intact?
Want to wrap up the year knowing what people actually need!
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X-Design
The biggest frustration for me is memory without control.
Most AI memory systems either remember too little (forcing constant context repetition) or remember too much in ways that are opaque and hard to correct. I often don’t know what is being stored, why it’s being recalled, or how to edit or expire it.
A few concrete pain points:
Low signal-to-noise: trivial details get remembered while important preferences or long-term goals are lost.
No lifecycle management: memories don’t age, decay, or get versioned as my context changes.
Poor portability: switching tools usually means starting from zero, even though the “memory” is supposed to be about me, not the platform.
Shallow understanding: systems store facts, not intent, constraints, or trade-offs — so recall often feels technically correct but practically wrong.
What I’d want is explicit control: visibility, editability, scopes (short-term vs long-term), and portability across tools. Until memory feels more like something I own rather than something happening to me, it won’t fully click.
AI Context Flow