Handing an agent's next-step decisions to Jev while Claude and GPT do the thinking
A tutorial shows routing an agent's branch decisions to Jev through the Typesafe SDK using choice, score and noul question types, at $0.42 per 10,000 decisions.
the cheapest upgrade to any ai agent right now is a model that can't write a single word the move: let claude and gpt do the thinking, and hand every what's-next call to a model that charges $0.000042 per decision all it takes is one api key and one python file: 1 → find the forks in your agent: enough sources, who works next, is it done. none of that needs a frontier model writing essays 2 → start in the typesafe playground, feed jev one task and one question, see a typed answer come back with a probability 3 → install the typesafe sdk and drop in the router script. each task gets sorted into a research, write or review queue on your machine 4 → pick the question type: choice for the next worker, score for source quality, noul for yes or no 5 → borrow browser use's trick and refresh the options after every step. that's how their agent found flights in 7s for $0.0039 6 → set the floor at 0.85 confidence. below that it comes back to you, and publishing always waits for your approval 7 → batch every question into one call. nothing billed for output, 10,000 decisions for $0.42 what changes: 4 paragraphs of thinking out loud turn into 5 typed answers. the llm writes, jev decides, code runs it most people will keep paying frontier prices for every yes and no. the ones who separate thinking from deciding end up with leaner, quicker agents grab the decision-layer setup and go through the full jev roadmap below ↓
This post quotes another post: “Long read: how to build a Jev-powered agent stack”