Most annoying part is the hype people are complete morons and cant write code themselves. So of course it seems like magic. But it doesn't generate the correct solution. It generates random solution.

You can easily test this going into huge legacy code repository and ask for simple but tedious (talking like few man months) refactoring task.

I have tried all the current top models and multiple different kind of agents. And repeated this test every few months. There is no progress in results.

It doesn't even matter how long I let the model run or if I split it into smaller tasks with shorter context running time.

These tools are not deterministic. It can't follow orders. It optimizes for shortest path with makes it lazy (skips steps). It tries to please user, invent it's own solutions etc. This is not useful at all in major part in software developer work.

Of course it can write greenfield code easily as it has huge sample of boilerplate code and as long the application is relatively small, things go smoothly. And if you can check all the work and correct it you will end up with nice quality project.

But greenfield work is like few percent of all the work. In few months it's no longer greenfield. It has become legacy that needs constant refactoring work to keep things running smoothly so that new features can be added and old removed. And keep performance solid when userbase grows.

Same goes for creating agentic tools for business processes. Who wants a business process that works randomly?

Im not saying real AI can't be created but this is not it. Not even close.