so I gave jev full control of the falcon-9 class rocket

Gave Jev full control of a Falcon 9 simulation in MuJoCo, letting it pick engine counts and burn timing across 12 runs for $0.04.

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so I gave jev full control of the falcon-9 class rocket

full launch to landing

no autopilot, no scripted trajectories, no safety veto in the code

every decision was made by jev ( you can see decisions at the bottom of the video)

and yeah it was able to land the booster

and all this with just 245 calls and and $0.04 in API calls

for sim I used mujoco

and the configurations were 42m booster, 425 tonnes, 9 engines, real atmosphere, mach dependent drag, wind and propellent depletion

the vehicle was going ubstable every .8 secs, and jev's decesion making takes place at ~1Hz and output in ~0.4 sec

so I gave jev these controls

> launch or hold

>engine count for every burn( it chose 5 for landing by itself !)

> when to light that burn

>ascent cutoff, coast, entry, legs, touchdown

so after giving all these controls to jev the experiments begun

and after 12 runs and tweaking multiple things it managed to land by itself

I will write a full article about it

and what I did with experiments and whet I tweaks I made

but for some final thoughts

people are saying it's just a classifier

yes, but it's a very good and effective classifier, and its speed and decision making, open up a whole new work for real life tasks and implementationa

I will also open source the whole repo for this after cleaning up the clutter in my code

so this is the short demo

I hope you like it

Engagement when collected

Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.