I am adding Jev to @AlbatrossCoding, and it could be a really interesting way to make my harness a lot more token efficient. Instead of just adding Jev as a model provider, I'm going to have essentially what I guess I'll call "Jev Mode" that allows you to leverage what a model like this is actually good at, i.e. making decisions. Right now, we waste a lot of time with agents having them perform lots of tool calls. I think Jev could essentially short circuit this in a way. The logic I'm adding will add a step where your prompt goes to Jev first. If it's a question with predefined answers, Jev can just answer it. Otherwise, it goes to an LLM, which can answer or use tools. I can benchmark this against a traditional harness to see what kind of performance gains it gets, my thought it is could be a lot faster and more token efficient for some tasks. Will share more once it's ready, but I'm also very open to changing my design here so please poke holes in it if you see a way I could improve. Hoping to make Albatross one of the first harnesses with Jev Inside™ 🪽 Diagram below of the flow I'm building out: