Community Java 17 client for TypeSafe's System One API with typed Noul, Choice and Score questions, lambda-style builders for nested criteria, status-specific exceptions and a Spring Boot starter.
Spring WebFlux starter that asks Jev whether HTTP 200 responses actually encode a failure, converting suspected silent failures into SemanticFailureException for existing error handling.
A lightweight, pluggable Java framework for CLI, HTTP, and modular applications that carries Jev, TypeSafe, and MCP-server topics; added from Maven as org.tinystruct:tinystruct and requiring JDK 17 or higher.
First @typesafeai use case, live in our Mac app: setup and troubleshooting help when no model is loaded.
Model downloading, load failed, API returning 503, phone won't pair: the user asks, Jev reads the question with the whole built-in manual as state and decides, withShow more
built `jev-review` @typesafeai
it's an experimental, local-first MCP plugin that gives coding agents a score quality feedback loop across different metrics.
agents call jev while they work, get scored, make improvements, and repeat the loop
try below 👇
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x
Now using @typesafeai Jev in aiseotracker.com, linkdr.com, genppt.com, etc
AI ends up vibe coding so much AI regex slop if you don't read the code, so I can finally move all this hard-coding to Jev and it's insanely fast!
Also for regular LLMShow more
got @typesafeai's new model Jev as a chief of staff for bots
Jev reads the task, wakes the right teammates off the bench
and gives each one the right model
It is possible on OpenMausBot as it supports all the LLMs from your existing subscriptions
Jev as a decision engine isShow more