A laptop with 16–32 GB of memory can answer questions about your own notes, code and unfinished ideas, and none of your data leaves the computer. Choosing the model is the easy part. Two other things decide whether the answers are useful: how much memory the model has, and how well it finds the right pages of your files. Without them, it just guesses, and it sounds sure even when it is wrong.
An artificial intelligence (AI) router sits between your app and the model providers and decides, per request, which model answers. "Router" names three different jobs — a gateway, a fallback chain and a smart router — and each hands over more of a decision that used to be yours.
For fifteen years the .env file has been the most convenient lie in web development: a plaintext file full of production-grade credentials, kept safe by the single assumption that only you would ever read your own disk. That assumption is now false, and the fix is less dramatic than it sounds.
TypeSafe AI launched Jev on 15 September 2026 with a headline of "193.6x faster, 444.6x cheaper" and a promise that it "can't hallucinate". Read the primary sources rather than the reposts and a narrower, more interesting product appears: a frontier-trained classifier for software, not a better large language model, with every number so far reported by the vendor.
The plugin built, packaged and published on the first try. I could not have explained the packaging step to anyone, and I shipped it anyway. After several months of building games, static sites, libraries and plugins with an artificial intelligence (AI) assistant doing most of the typing, that sentence is the whole story: producing code stopped being the hard part, and something else moved into its place.
I opened Claude Code on a side project after a day away, and it greeted me with a careful reconstruction of what we had been doing, pieced together from the notes file and the working tree. It was right, but it was a guess. The whole conversation that produced that work was sitting on disk, one command away. Here is how sessions actually persist, what a resumed one gives you back, and what it never will.
When a coding agent writes most of the code, reading every diff stops being realistic, and "reading diagonally" — skimming — becomes the default. It is a real bet, not a safe one: architecture doesn't break in any single diff, it erodes across all of them, and skimming checks exactly the part that was never the problem.
Every strategy for surviving the flood of machine-written pull requests optimizes the same thing: catching bugs. The research on code review says catching bugs was never the job it was best at.
A tweet doing the rounds says LinkedIn merged four job titles into one. The quote is real, the role is real, and the arithmetic everyone read into it is not — and the difference is the whole career signal.
Claude Code writes two records to your disk: an append-only ledger of every exchange with the model, and a small cached snapshot of how full your rate limits are. Almost every tool and blog post about local usage tracking knows about the first one and misses the second — including, until I actually looked, me.