Effective AI agents require both immediate memory for current interactions and long-term memory that integrates user history, preferences, and institutional/team knowledge to provide personalized, context-aware experiences while reducing computational costs.
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The Secret to Truly Personalized AI Agents #ai #aiagents #agenticai #enterpriseai #tech追加:
I think memory is going to be more and more important over time.
And it's not only about your current agent's memory, but also about how do you integrate previous data of your user with your current agent?
So that it's integrated as a context together.
So your agent so because your user would expect, "Oh, I'm using your new product agent. It definitely knows my previous things, my previous preference and so on, right?" So I think the hard part is really about really making the agent intelligent requires a lot of context. And the immediate memory is just one part. But the long-term memory um it's really I I like the idea about it's everything is user driven. Have to have personalized you a memory for each individual user and how you can actually structure them in a more efficient way.
>> And actually to to expand on that, there's also the notion of institution institutional memory and team memory.
>> Which is true.
>> So you can imagine you you're in a team just like in software engineering team, right? So if I'm going to do something, I ask some other people in the the team because some of them might have done something similar before.
And so then they may even have code for me to to start with, right? So So it seems like uh anything that can reduce the amount of tokens that we burn >> And also like increase the context awareness.
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