There is more to a program then writing logic. Good engineers are people who understand how to interpret problems and translate the inherent lack of logic in natural language into something that machines are able to understand (or vice versa).
The models out there right now can truly accelerate the speed of that translation - but translation will still be needed.
An anecdote for an anecdote. Part of my job is maintaining a set of EKS clusters where downtime is... undesirable (five nines...). I actively use chatgpt and copilot when adjusting the code that describes the clusters - however these tools are not able to understand and explain impacts of things like upgrading the control plane. For that you need a human who can interpret the needs/hopes/desires/etc of the stakeholders.
Let's be clear - current AI models are being used by poor leadership to remove bad developers (good ones don't tend to stick around). This however does place some pressure on the greater tech job market (but I'd argue no different then any other downturn we have all lived through).
That said, until the issues with being confidently incorrect are resolved (and I bet people a lot smarter then me are tackling the problem) it's nothing better then a suped up IDE. Now if you have a public resources you can point me to that can look at a meta repo full of dozens of tools and help me convert the python scripts that are wrappers of wrappers( and so on) into something sane I'm all ears.
I highly doubt we will ever get to the point where you don't need to understand how an algorithm works - and for that you need to understand core concepts like recursion and loops. As humans brains are designed for pattern recognition - that means writing a program to solve a sodoku puzzle.