ReMyndyour ai conversations are part of your work now
something changed about how people use ai, and the tooling has not caught up.
it stopped being a lookup box. per the anthropic economic index, 51.4% of ai usage is now augmentation rather than automation: not "give me an answer" but long, iterative back and forth where a person and a model work a problem together. you are not querying. you are thinking, out loud, in a text box.
which means a real amount of your actual reasoning now happens inside a chat window. and then the tab closes.
what is actually lost
not the answer. you usually keep the answer, or the code, or the paragraph. what disappears is everything around it.
the path. the four approaches you tried before the one that worked. next month you will consider one of those four again, having forgotten you already ruled it out, and why.
the constraints you established. twenty minutes of context you fed in: the schema, the requirements, the thing the client said, the reason this cannot use that library. recreated from scratch every session, because the tool starts empty.
the reasoning behind the decision. you asked which of two options was better, got a good comparison, and picked. six weeks later someone asks why. the answer was in a conversation, and the conversation is gone.
the small corrections. every "no, not like that, because…" is a piece of judgment you supplied. it shaped the output and then evaporated.
if this happened in a meeting there would be notes. it happens in a chat window and there is nothing.
why provider history does not fix it
every ai tool keeps a list of past conversations, so on paper this is solved. in practice it is not, for three reasons.
it is fragmented. your thinking is split across whichever tools you used. one for code, one for writing, one built into an editor. no single history contains your work.
it is not really searchable. these histories are lists you scroll, not indexes you query. finding the session where you worked out the caching strategy means recognising it in a sidebar.
it is isolated from everything else. the conversation happened alongside a doc, a dashboard, a call, three tabs of documentation. the provider saw the chat and nothing else. the context that made the conversation make sense is not in it.
and it belongs to the provider. switch tools, lose a subscription, or watch a company get acquired, and it goes with them.
the shape of the fix
the useful move is to stop treating ai chats as a special category of data that lives with whoever provided the model, and start treating them as what they are: work you did on your screen, like every other thing you did on your screen that day.
capture at the screen level does not care which tool you used. it records the session, not the service. and because it captures everything else at the same time, the conversation stays connected to the doc you had open, the error you were chasing, and the call an hour earlier where the requirement came up.
that is the thing provider history structurally cannot do. it only ever sees its own window.
what this looks like day to day
"what did i decide about the retry logic, and what did i reject?" the session, the alternatives, the reason.
"pull up the conversation where i worked out the pricing model." found by what it was about, not by scrolling a sidebar.
"what was i actually working on last tuesday?" the chats, the docs, the calls, in one timeline, in order.
"why did we go with this approach?" answerable again, months later, from your own reasoning rather than reconstruction.
the obvious objection
recording everything you type into an ai is a serious thing to do, and you should be suspicious of anyone casual about it. these sessions contain half formed thinking, client details, unreleased work, things you would not say in a meeting.
which makes where the archive lives the entire question, not a footnote.
remynd captures and runs ocr on your mac, and stores the archive locally by default. you can point the ai at a local model through lm studio so answering happens on your machine too. cloud backup is optional, encrypted, and exportable to an s3 bucket you own. and you can exclude specific apps, sites or keywords from capture entirely, applied locally before anything is stored.
the honest scope of the claim: your captured memory is never in our cloud. it is on your machine or in your bucket, never pooled, never trained on, never sold.
the point
the way people work with ai moved faster than the tools for remembering it. more than half of ai usage is now collaborative sessions rather than one shot queries, which means a growing share of professional thinking happens somewhere with no memory attached.
your notes app has a memory. your codebase has a memory. the place you now do a lot of your actual reasoning does not.
if you write code, remynd for engineers covers the local model setup. if you are comparing tools, start with rewind ai alternatives.
download remynd free for mac → free to download, runs locally, no card.