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The things your AI remembers about you turned out to be worth money.
Stuff that's worth money usually ends up owned by somebody.
It should probably also be you.
Your laptop is never going to train a frontier model. It doesn't have to.
A lot of AI's daily work is small and frequent. Drafts, summaries, cleanup, checks that can wait a minute.
Work like that doesn't need a datacenter. It needs whatever's nearby, switched on, and not busy.
Confident answers and correct answers look identical in the moment.
The wrong ones are formatted exactly like the right ones, which is the whole problem with taking any single AI's word for something.
Checking has to come from outside the thing being checked.
That's true in courts, in science, in accounting. AI won't be the exception.
The AI buildout has two possible supply curves.
Datacenters need land, power deals, water, and years in a grid queue.
The other is already in your house.
Computers and devices plugged in, AND idle most of the day.
Only one of these gets any attention. 👀
Every project, client, company comes with a context tax.
The thing is, that context already exists, complete, in their own drives, docs, tools and chats.
why can't that be one shared space?
The best work happens when everyone can build on what everyone else knows.
Importing ≠ portability
The big AI models will now let you export your chat history and import it somewhere else.
But there’s two catches.
1. It only works between the big models. The smaller AI tools in your stack never see any of it.
2. It's a file dump, not a sync. Every time your context changes, you're updating it by hand.
Context should be portable everywhere you work, instead of being held together by a million little workarounds.
How often do you find yourself repeating things to AI?
Context is a badly managed resource because a lot of the time you're still moving it by hand.
You explain what you're working on in one tool. Then again in the next, and the one after that.
We think that loop needs to change.
Improving AI context uses fewer tokens and gets better answers.
Dump your whole history into every prompt and you'll easily burn 25,000 tokens.
Pull only what matters and you cut that by 80%+.
Memory needs to sit on its own layer, where your tools can plug in on demand.