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    Scobleizer outlines desired AI assistant memory features

    Tech commentator details features like surfacing relevant past conversations and connecting industry changes to user projects.

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    11 Sources, ,

    TLDR

    Robert Scobleizer posted multiple times about the AI capabilities he wants, including surfacing a person's past statements that alter a meeting's context and linking industry shifts directly to his own work. He highlighted the founder of Today AI, who has spent over a decade developing tools to help people focus on what matters, first in mobile collaboration and now in AI. Scobleizer also referenced a post by @ashwingop arguing that memory becomes the moat once models commoditize. Rohan Paul replied that deciding which history should still shape the next answer remains difficult.

    Combined views

    297.8K

    11 Sources, first seen 24d ago

    Combined views

    297.8K

    11 Sources, first seen 24d ago

    439 likes
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    24d ago
    first seen 24d ago
    439 likes
    101 comments
    188 saves
    60 reposts
    101 comments
    188 saves
    60 reposts

    Sentiment

    Positive63.6%36.4%Negative

    Summary

    Sentiment

    Positive63.6%36.4%Negative

    Positive accounts welcomed AI that understands what matters to users and acts without constant steering, while negative accounts shared frustrations with systems missing intent or wasting effort on irrelevant tasks.

    Based on 23 sentiment-bearing replies from 22 accounts across 3 conversations.

    Summary

    Positive accounts welcomed AI that understands what matters to users and acts without constant steering, while negative accounts shared frustrations with systems missing intent or wasting effort on irrelevant tasks.

    Based on 23 sentiment-bearing replies from 22 accounts across 3 conversations.

    11 Sources

    @ScobleizerHere's what I actually want from an AI assistant. Before a meeting, surface the thing that person told me three months ago that changes everything about today's conversation. When something shifts in my industry, connect it to what I'm actually building — not just flag it. Understand that something I was obsessed with in January might be completely irrelevant now. That's not a memory problem. That's a judgment problem. It takes learning how priorities change. Which people matter. When to interrupt. When to disappear. An assistant that remembers everything but keeps surfacing the wrong things isn't an assistant. It's noise with a good memory.
    @rohanpaul_aiYou reopen the same project, explain again why you killed an approach last week, and the AI recommends the exact same thing. That’s the fatigue. Remembering the history helps. Knowing which parts of that history should still change the next answer is much harder. I don’t need an AI that remembers everything I’ve said. I need one that knows what has changed, what still matters, and what doesn’t. It’s not that I don’t know how to use it. It just doesn’t know me. That’s what caught my attention about what @TodayAIofficial is building.
    @kimmonismusAn AI can complete a task perfectly and still spend your time on the wrong thing. Imagine an assistant preparing notes for tomorrow’s meeting. A message arrives that changes the deadline, and suddenly another project needs your attention first. The notes may be excellent. The assistant still needs to recognize that your priorities have changed. As AI takes on more work, these decisions become increasingly important. Which task should come first? When is an interruption justified? When should the system ask you? That’s the question behind @TodayAIofficial’s approach to personal AI: how can an agent learn what matters to a particular person and use that context throughout the day? Memory is part of the answer. Remembering a deadline helps. Connecting it to a promise you made last week, noticing that the plan has changed, and bringing it up while you can still act takes more. It also requires a way to correct the system. People change their minds. A preference from three months ago may no longer apply. An assistant should make its assumptions visible and let you update them. I think this is a useful direction for personal AI. There’s considerable value in software that can connect scattered information and help you decide where to focus. The test will be how well it handles an ordinary, messy day: catching the commitment you might miss, explaining why it needs attention, and leaving the decision with you.

    11 Sources

    @ScobleizerHere's what I actually want from an AI assistant. Before a meeting, surface the thing that person told me three months ago that changes everything about today's conversation. When something shifts in my industry, connect it to what I'm actually building — not just flag it. Understand that something I was obsessed with in January might be completely irrelevant now. That's not a memory problem. That's a judgment problem. It takes learning how priorities change. Which people matter. When to interrupt. When to disappear. An assistant that remembers everything but keeps surfacing the wrong things isn't an assistant. It's noise with a good memory.
    @rohanpaul_aiYou reopen the same project, explain again why you killed an approach last week, and the AI recommends the exact same thing. That’s the fatigue. Remembering the history helps. Knowing which parts of that history should still change the next answer is much harder. I don’t need an AI that remembers everything I’ve said. I need one that knows what has changed, what still matters, and what doesn’t. It’s not that I don’t know how to use it. It just doesn’t know me. That’s what caught my attention about what @TodayAIofficial is building.
    @kimmonismusAn AI can complete a task perfectly and still spend your time on the wrong thing. Imagine an assistant preparing notes for tomorrow’s meeting. A message arrives that changes the deadline, and suddenly another project needs your attention first. The notes may be excellent. The assistant still needs to recognize that your priorities have changed. As AI takes on more work, these decisions become increasingly important. Which task should come first? When is an interruption justified? When should the system ask you? That’s the question behind @TodayAIofficial’s approach to personal AI: how can an agent learn what matters to a particular person and use that context throughout the day? Memory is part of the answer. Remembering a deadline helps. Connecting it to a promise you made last week, noticing that the plan has changed, and bringing it up while you can still act takes more. It also requires a way to correct the system. People change their minds. A preference from three months ago may no longer apply. An assistant should make its assumptions visible and let you update them. I think this is a useful direction for personal AI. There’s considerable value in software that can connect scattered information and help you decide where to focus. The test will be how well it handles an ordinary, messy day: catching the commitment you might miss, explaining why it needs attention, and leaving the decision with you.