Comment by shoman3003

Back to stories Open in a window

Comment by shoman3003

i was building an agent to do outreach, but while i was leaning how basic memory works with letta - i noticed something; all memory architecture (letta/claw/claude) simply moves the pain to retrieval.

I started looking back at my own memories trying to understand how my mind remembers stuff as opposed to how agents do, and then i came across a pg essay that mentioned something similar.

Human memory doesn't store images in full resolution; just think back to any old memory you have - it's barely visible (100*100res). The older the memory is, the lower the resolution is. Faces are usually blurred; the images are there for context not for clarity. Same with text, when i look back at an old conversation, i don't remember most of the stuff that was said nor do i remember a "summary" of what happened. My memory of conversations is a lot like my memory of images; one part is ultra clear while the other parts are blurred (pain=weights).

Why would our minds blur stuff if they are saved to long-term memory! if my 10-year-old laptop has 500gb storage, my brain definitely has many terabits if not x100 that! Why do i have to relearn a skill that i used to be very good for years when i clearly remember almost all of the steps to how to do it. This sounds a lot like a context memory that went through compaction & then dumped to the disk. Even tho the log has been saved to long term memory; it's no longer usable unless rebuilt into a new context again, which is why i need to relearn the skill.

ONE POSSIBLE EXPLAINATION why the brain needs to care about memory saving to this a degree that it has to forget all of the details about my first car except its color & brand. It's that our biological memory is operating more like a set of context windows that switch between each other not retrieving data from a permanent long-tern storage!

Which means that we switch back and forth between different specialized context windows while we work (which is why we can switch takes in less than 60sec). Unless the context window is dumped into the long-term memory, we can still load it fast. The brain doesn't dump current sessions unless something major happened, when we change career, cities or we go through something big.

Whenever i am in a new city it feels like a new context window has loaded into my brain, my childhood memories suddenly feel different, the stuff relating to a different career i had in the old city feel alien. The new context window even makes me think in a different lens & analyze stuff from a totally different angle.

Why are we not doing the same with Ai, why do all memory structures either remove the full old sessions entirely or summarize them into oblivion? why not do what the brain is already doing & spread the work across 100s of context windows that each is concerned with 1 thinking pattern?!

Replies shoman3003 · 2026-06-23
Open on HN
Loading the discussion…

Domain filters

Stories from these domains are hidden from every list. Subdomains match too: blocking substack.com also hides danluu.substack.com.

    About YAVCHN

    YAVCHN is a reader for Hacker News and Lobsters, with articles and discussions in separate windows or Classic pages.

    Created by Paul Parks and built with PUDL.

    YAVCHN source code on GitHub

    Help

    Keyboard

    j / k
    Move down and up the story list. The arrow keys scroll whatever has focus.
    Enter
    Read the marked story in the article reader.
    ]
    Read the next story in the same article-reader applet. Back returns to the previous story.
    p
    Pin or unpin the marked story, which keeps it in Pinned.
    n / N
    Move to the next or previous top-level comment in the window in front.
    c
    Collapse or expand that comment.
    f
    Hide or show the story list.
    Esc
    Close a menu or this help.
    Access key m
    Go to the menu bar. Most browsers take it with Alt on Windows and Linux, and Safari with Control and Option.
    ?
    Show this help.

    Windows

    Each story opens in a window holding its article above its discussion; drag the bar between them to share the room differently. A window can be moved by its title bar, resized from any edge, snapped to a half or a corner by dragging it there, maximised, or minimised to the bar at the foot of the page. Use Window > New reader window to open an empty reader, or Story > Open in new reader window to open another reader for the current article. Docked readers keep their articles when you select another story from the sidebar. Minimized readers can be restored and reused for their site. A window's Next story link reads on down the list in the same window.

    A link in a comment or an article to another Hacker News or Lobsters thread opens that thread in a window too. A link to a single HN comment opens the comment above its replies.

    While a story's window is in front, the Story and Discussion menus in the menu bar hold its commands: pinning, Next story, sorting, collapsing every thread, jumping to the first new comment. Each window also remembers where you were in its article and discussion, so a reload, or Back to a story that Next took you past, finds your place again. Closing a window forgets it.

    The whole arrangement lives in the address, so a bookmark or a shared link brings it back, and Back undoes the last change. Moving between Hacker News, Lobsters, their lists, Pinned and Find changes only the list, and leaves the windows open.

    The list

    The pin at the start of a row keeps the story in Pinned, and the cross at its end hides it. Pinned can be narrowed by words in the title, site or author, by source, and to the stories you haven't opened yet, and ordered by when you pinned them, by points or by comments; the filters are part of the address, so a filtered view can be bookmarked. Scroll past the end of the list to load more. Domain filters, in the View menu, hide every story from a site.

    Browsing view

    View > Windowed and View > Classic select the browsing view and save your default in this browser. Window view reuses a reader for each feed. Classic view opens stories and applets as pages. Open as a page and Open in a window are one-off actions that do not change your saved default. Direct page links always open as pages.

    Applets

    The Applets menu in the menu bar holds three tools, each a window of its own. Replies to me takes your Hacker News user name and lists the replies to your last thirty comments and stories, checking again every three minutes while it is open, and marking what is new since you last marked them read. Look up a user opens a profile on Hacker News or Lobsters, with their submissions and recent comments, as a commenter's name in any discussion does; the bar at the top of a profile looks up someone else in the same window, and Back returns to the one before. Who is hiring? filters the posts of HN's monthly hiring threads by the words you type.

    They read only what the sites publish to everyone, so none of them asks for a login, and your user name stays in this browser.

    Find

    Find takes any link and lists every time it was submitted to Hacker News and Lobsters, so you can read each discussion of it.

    About

    YAVCHN never sees your Hacker News or Lobsters login. The discussion is fetched from each site's public API; to vote or reply, follow the link above the discussion, or the arrow beside a comment, to the source's own site. Pins, hidden stories, filters and layout are kept in this browser only.

    Open source: github.com/paulmooreparks/yavchn. Built with PUDL.