Routing with Jev is cheap and quick. Whether it helps depends on catalog descriptions nobody has tested, and on failures that won't show.
Jev takes text in and gives no text back. You send it a block of state (a string, a JSON object) and a set of typed questions.
Multi Token Prediction is being sold as a free speed hack for local LLMs. Flip one flag in your inference engine and generation speeds up by anywhere from a quarter to a factor of three, at no cost in output quality. That pitch is accurate as far as it goes. However, there is an interesting...
Which model should run this task? The question has a correct answer. It arrives after you have stopped needing it.
Token pricing treats every token as interchangeable: one model's tokens against another's, dollars per unit, compare and choose.
A widely shared post is making the rounds with an urgent pitch: ask Fable to write down its "operating manual" while it's still free.
Every few weeks a fresh list of "secret" Claude slash commands makes the rounds - in newsletters, on LinkedIn, on Twitter in Instagram reels.
AI cost is turning out to be a control problem, not a pricing problem — and the only place to fix it is the gateway.
How Fork-on-share doesn't give you a URL to update. Why the Fork-on-share model is still working well for many use cases.
Thariq, Karpathy, Theo — HTML for LLMs has crossed into the open. But the rediscovery is only the read side. The write side is where the document edits itself.