jev-decision-layer

varun bhardwaj

@varunPbhardwaj · Sep 29

Qualixar Jev Decision Layer adds recipes, MCP tools, and optional local Laya

I've been watching something interesting happen over the last couple of weeks. My GitHub and X feeds are suddenly full of Jev and Laya experiments. People are showing routing. Token reduction. Local inference. Fast typed decisions. And honestly, I think the underlying idea matters much more than another model launch. TypeSafes Jev is built around a very different primitive : state + a bounded question → typed probabilistic decision. Choice. Score. Noul.TypeSafes Own System One workflow evaluations report 193.6× faster and 444.6× cheaper than their LLM reference on those workflows. Laya and Laya-MLX have made the same idea interesting locally as well, with very fast typed decisions running on Apple Silicon. But while watching all these demos, I kept coming back to one boring question: How does somebody actually USE this every day? Not just an AI researcher. A manager. A developer. A freelancer. A content creator. Because a fast model call is not a workflow. Someone still has to decide: Which bounded question should I ask? What are the allowed choices? Can this data leave my machine? Which provider should receive it? How confident is confident enough? What happens when the answer is uncertain? Who is allowed to execute the recommendation? And six weeks later — can I see what decision was actually made? That was the missing layer for me!!! So I built Qualixar Jev Decision Layer. Not another Jev demo. A reusable layer around the decision primitive. The current open-source release contains: → 38 reusable decision recipes → 20 MCP tools → 5 agent-harness adapters → 114 offline fixtures → hosted Jev + optional local Laya → local policy gates → inspectable decision receiptsAnd the recipes are no longer only developer examples. A manager can evaluate a work item against supplied priorities. A creator can choose between a Short, newsletter or carousel from a brief. A freelancer can route an enquiry. A developer can narrow tools, files, skills, tests or review attention. Same basic primitive. Different decision recipe. One shared layer. There is another boundary I care about: the model does not get execution authority.Jev or Laya can recommend. The local layer can evaluate that recommendation. The host — Codex, Claude Code, VS Code, Hermes or Antigravity — still owns the actual action and its permissions. I think the architecture becomes obvious once you see the whole loop: context → recipe → Jev/Laya → local gate → advisory result → receipt → host Thats the layer I felt was missing! Repository: Particularly interested in one question: What bounded decision are you still wasting a frontier-model turn on today? #opensource #jev #typesafe #laya