And well if they are there they might as well fly for practise.
And no. I would not allow LLM in to the loop of making any decision involving actual flying part.
Much of the value of a human crew is as an implicit dogfooding warranty for the passengers. If it wasn't safe to fly, the pilots wouldn't risk it day after day.
To think of it, it'd be nice if they posted anonymized third-party psych evaluations of the cockpit crew on the wall by the restrooms. The cabin crew would probably appreciate that too.
Furthermore, the concept of "ejecting a passenger" from a flight would mostly not be something you do while in the air, unless you're nuts. Ejecting a passenger is either done before takeoff, or your crew decides to divert the flight, or continue to the destination and have law enforcement waiting on the tarmac.
Naturally, pilots get involved when it's a question of where to fly the plane and when to divert, but ultimately the cabin crew is also involved in those decisions about problem passengers.
It absolutely can; it's called autoland[1]. In really bad visibility, pilots simply can't see the runway until too late, and most aerodromes which expect these conditions have some sort of autoland system installed. The most advanced ones will control every aspect of the plane from top-of-descent (TOD), flaps and throttle configuration, long and short final, gear down, flare, reverse thrust, and roll-out, all the way to a full stop on the runway. Zero pilot input needed.
And most of this was already available in the late 1970s. We have absolutely no need for LLM-based AI in aviation; traditional automation techniques have proven extremely powerful given how restricted the human domain of aviation already is.
never mind that most crashes are caused by humans, very rarely by technical issues going amok
Because humans are the fallback for all the scenarios that the tech cannot reliably cover. And my intuition says that the tech around planes is so heavily audited that only things that work with 99.999...% accuracy work will be left to tech.
Seeing how Claude (or any current LLM) perform in even the most low-stake coding scenario I dont think I would ever set foot on a plane where the 1% of most risky scenarios are decided by one.
I mean if you have a stable plane, then it'll do alright, as it'll mostly fly straight and level (assuming correct trim) reacting to turbulence however, the sampling rate would probably too slow, so you'd end up with oscillations.
For recognising that you're in a shit situation, yeah, it'll probably do that fine, but won't be able to give the correct control inputs at the right time.
Even that im not sure of, I know relatively little about aviation safety but I can imagine that there are all kinds of 0.0000000001% percent corner cases that no plane has ever encountered that still need some sort of reaction, who knows how easy an llm can distinguish those from the 0.000000001% corner cases that no plane has ever encountered that are completely fine and can be ignored.
However its as far as I know the check list volume scales with how "airline-y" the plane is. so for a one seater, the checklist is small and only handles a few things. For a 777 its a binder.
Most of the time. Sometimes you get a double bird strike when you've barely cleared the Hudson river, or similar.
I try to fly about once a week, I’ve never really tried to self analyze what my inputs are for what I do. My hunch is that there’s quite a bit of I(ntegral) damping I do to avoid over correcting, but also quite a bit of D(erivative) adjustments I do, especially on approach, in order to “skate to the puck”. Density going to have to take it up with some flight buddies. OR maybe those with drone software control loop experience can weigh in?
(d'oh, should have read the specific context: in the case mentioned, it is where the system acts as an integrator (pitch -> altitude), and so pure P control is pretty reasonable)
Gold
"spawning 5 subagents"
"500 Our Servers Are Experiencing High Load"
"500 Our Servers Are Experiencing High Load"
"500 Our Servers Are Experiencing High Load"
You'd want all the data from the plane to be input neurons, and all the actions to be output neurons.
It would still be better just to let autopilots do the work, because the point of the exercise isn't improved avionics. But it would be an honestly posed challenge for LLMs.
I wouldn't trust Claude to ride my bike, so I certainly wouldn't board its flight.
This is where I think Taalas-style hardware AI may dominate in the future, especially for vehicle/plane autopilot, even it can't update weights. But determinism is actually a good thing.
The author tried getting Claude to develop an autopilot script while being able to observe the flight for nearly live feedback. It got three attempts, and did not manage autolanding. (There's a reason real autopilots do that assisted with ground-based aids.)
Related from December 2025: Garmin Emergency Autoland deployed for the first time
https://www.flightradar24.com/blog/aviation-news/aviation-sa...
Large planes are autolanded in normal conditions with oversight of qualified, capable and backed up operator, in harsh conditions they are not used, as far as I understand.
Autoland systems in small planes are emergency systems to land plane with disabled operator in any conditions generally acceptable for flying in that plane.
Using Claude sounds overkill and unfit the same time.