X posts

remade an AI filter composer I was working with, using Jev instead of Luna Medium, numbers are good, can probably iterate a bit to make it cheaper and faster https://t.co/pFGsRa456G

Vibe coded a parallel search using jev for agents, planning to hook up a local LLM to this to get human output. Discovers new pages and adds them to a BFS queue, jev consumes pages in parallel, reranks and adds to the queue. https://t.co/EkpZhuYmRB

🚨 I gave the Trump vs Kamala debate a live BS meter using Jev every sentence, both candidates, 5 yes/no questions each 1,191 Jev calls / 1.18M tokens / 415 ms median total cost : $0.0497 same questions for both, clips picked by one fixed rule, not a fact-check https://t.co/m8u4ALl6Me

using jev and the sick new markdown renderer in @pidotdev , i made a pi-extension that lets you toggle how much detail you want in the agent output. this was motivated by my inability to understand what opus 5 was getting at https://t.co/PE4HQhc84T

IRS O*NET job classification using Jev (1,016 possibilities) Query: "I scoop scoops and sprinkle sprinkles" Result: 35-3023.00 Fast Food and Counter Workers https://t.co/SSXUqQwNo3

these are results of using jev on one of our security pipelines. we already have to use smaller (and dumber) models to make it economic and this model does it over 5x cheaper, faster and while maintaining much higher accuracy. i don't normally hype over new model releases but that's the first one that actually impressed me. good job @typesafeai

I'm using Jev (from @typesafeai) to categorize expenses for my company! Our office manager used to do this. It's all in Mongolian and we have to do it using bank records. It is very unique to our company, and not something a software would handle easily. We also have about a years worth of Excel files (training data) that I'm using to give Jev guidance on classification (few shot style). It really works, it's stupidly cheap, and when it's not confident it says so. Pretty great! This isn't anything new, classification in ML is extremely "solved". But this is a general classification model