AI agents spend a ridiculous amount of compute generating text nobody actually needs. The decisions an agent makes along the way don’t require a written answer and yet, agents still send them to generative models, wait for an answer while burning through tokens and then parse that output back. The overhead is already drawing scrutiny — OpenAI’s own researchers recently disclosed spending $7,000 a day running agent workloads . Kev, a new family of open decision models built on Qwen 3.5, takes a different approach and skips the generation entirely. Developer Jared Palmer released a new...

Source: The New Stack