Astra is incredibly dumb and annoying to work with on "high" reasoning, for doing fairly well known distributed systems things, nothing majorly exotic, it still makes absolutely braindead decisions like deciding to re-use a random nonce field which I've already discussed with it that has a very particular temporary purpose and will probably be removed later, but it still thinks its a great idea to re-use that field not only as a different id in the same message, but to re-use it as the only semantic id for one particular type of sub message. This is when I'm walking it through an api design document and it has plenty of documentation plans it can pull in and a very clear direction of the project. If it was a junior engineer I was trying to get to help out I would probably get brain damage from the amount of times I'm face palming myself and I definitely would not hire them, and this is a small greenfield project with me going through it step by step. I did try giving it longer horizon tasks and had to throw out the entre work.
I mean maybe its a skill issue on my part, and I'm sure astra will get much better at coding but at the moment its useful in that I don't have to write the code or setup the build scripts or test fixture boilerplate but there is absolutely no way I can just give a (fairly well specified) goal and let it run and expect it to make good design and implementation decisions. Fable probably better but doing something outside of their training distribution that's not the equivalent to cloning an example unreal project or whatever is pretty disastrous unless you are directing it very closely.
The exception of course is, cyber , and its very obvious why. Its trivial to create RL environments that create bugs and then have an isolated environment and let the models try break it. This is not at all surprising, finding vulns and exploits IS just brute force work. That's why so many (blackhat/hardcore/unicorn-colored/greyish alien) hackers are basement dwellers. Its just a matter of putting in the time and mashing every combination until you find something that looks weird, spending days on that and then rinse repeat. It's brutally exhausting work that requires a certain level of knowledge and a shitload of determination and stamina and for humans, almost always an external source of motivation to keep going.
For humans that has always been a respected thing, dedication, determination, persistence, these are words we use for humans brute-forcing solutions and not giving up until they find the solution or die trying.
Personally I'm yet to see any evidence of LLMs doing anything interesting but (heuristically) brute-force problems and be very good at text and natural language to a level that is very very useful. I've no doubt that what we discovered with Auto Regressive LLMs is incredibly important so I'm not a skeptic, but I think its very hard to measure where we are with so much subjective information around.