LangChain's engineering post, two days after launch, wiring Jev into an agent harness as middleware in two places: choosing the model per request, and checking a tool call for risk before it runs, the same job Vercel's fx safety reviewer does. Both are LangChain middleware.
Sydney Runkle and Hunter Lovell, LangChain, in langchain.com
A simple lookup doesn't need the same model as a difficult debugging task. Model-routing middleware lets Jev assess the request and choose a model based on criteria you define, so fast and inexpensive for straightforward tasks, more capable for complex ones.
[...]
AutoModeMiddleware uses Jev to check tool calls for risky decisions it may take, and block calls before the tool executes.
Andre Landgraf's showcase of the yes/no gate, several worked examples at the link.
Andre Landgraf
1h
Ok, jev is really cool. So many great use cases where a fast and accurate yes/no gate can deliver meaningful performance gains.
Played around and built some showcase examples here →
Vipul Sharma's Minecraft agents ask Jev whether to fight or run, from what the agent can see, the mob count, its weapon and its health; one broke off mid-fight as the odds turned.
Vipul Sharma
1h
I hooked up Jev by @typesafeai to a few agents on my Minecraft world. Look at how Jev decides when they should fight and when they should run away.
Jev rates the odds from what the agent can see, mob count, weapon, how hurt it is, and runs away when they are bad. One broke off mid-fight as its odds turned.
Mahmoud's simulation of fifteen autonomous drones through an asteroid field, Jev deciding for each in under 300 ms, all fifteen arriving.
Mahmoud
2h
Jev can control a swarm of 15 autonomous drones in real time!
I built a simulation to test it navigating an asteroid field:
• Decision latency: < 300ms
• Survival rate: 100% (all 15 reached the destination)
Built with @typesafeai by @CompleteSkeptic
