Jev Engineering is the layer most agent stacks are still missing. state → decision → action → verification → next state up to 193x faster and 444x cheaper in our tests. everyone is optimizing the model. Jev Engineering optimizes what happens between model calls. every agent eventually hits the... same fork: state → multiple possible actions → one route has to win instead of sending every decision back to an expensive LLM call, Jev turns that into a dedicated layer: so the loop becomes: LLM → reason Jev → decide tools / agents → execute state → update Jev → decide again once decisions become their own engineering layer, you can benchmark, batch and verify them separately. full blueprint in article ↓show more

I’m sorry for people who really miss it

lol, me too

It’s really new meta Ricker, banger article

fact bro

Saved g!

a model that refuses to write prose, finally

yep man

When Jev loops?

what a visual Ricker

@0xRicker hitting the nail on the head with this. I found optimizing between model calls made a huge difference in my own builds too.

if decisions become their own layer, who writes the ground truth you verify them against?

optimizing the process between model calls is key to efficiency gains

the important split is state versus a decision. state tells you what happened. a decision needs a reason, source, and expiry, or the next loop just repeats yesterday's mistake.the important split is state versus a decision. state tells you what happened. a decision needs a reason, source, and expiry, or the next loop just repeats yesterday's mistake.

state transitions are expensive. routing every decision through the model is why latency hurts. what is the actual mechanism that cuts 193x?

the glue between model calls is where most of my agent bugs show up. the model itself was rarely the problem.

« up to 193x faster and 444x cheaper in our tests » from which model?

The control-layer thesis is right: most agent stacks waste a model call deciding what to do next. The real benchmark is whether verification catches bad state transitions cheaply enough to make that loop dependable, not just faster.

optimization layer is literally what agents need right now

Optimizing the overhead between model calls is where the real multi-agent scaling happens

Jev is an if-statement and a waste of time, stop deepthroating the hype cycle

Chuẩn luôn fen ơi, đợt này mình cũng thấy thế :))

把 state → decision → action → verification 显式化，确实比把所有控制逻辑塞进提示词更容易优化。尤其要把状态、预算和终止条件作为运行时数据记录下来；提示词只描述目标，系统才能比较不同策略的成本与可靠性。

everyone optimized the brain and forgot the nervous system

Jev engineering so popular now

Everyone's sleeping on Jev.

optimizing the gap between calls is the real claim not another model swap

Thank you very muchaa 👏