Ilias Ism runs several small products and had accumulated the regex that AI-assisted coding leaves behind. He is moving those rules to Jev calls across aiseotracker, linkdr and genppt, and says that where it replaces an ordinary LLM call it is around ten times faster and half the price.
Ilias Ism
Now using @typesafeai Jev in http://aiseotracker.com, http://linkdr.com, http://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 LLM calls, it is around 10x faster, 50% cheaper
Andre Landgraf's showcase of the yes/no gate, several worked examples at the link.
Andre Landgraf
2h
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
2h
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
3h
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
