If your project is very small, and it’s possible to feed your entire code base into an LLM in the near future, then you’re in trouble.
Also the problem is the LLM output is only as good as the prompt. 99% of the time the LLM won’t be thinking of how to make your API change backwards compatible for existing clients, how to help you do a zero-downtime migration, following security best practices, or handling a high volume of API traffic. Etc.
Not to mention, what the product team _thinks_ they want (business logic) is usually not what they really want. Happens ALL THE TIME friend. :) It’s like the offshoring challenge all over again. Communication with humans is hard. Communication with an LLM is even harder. Writing the code is the easiest part of my job!
I think some software development jobs will definitely be at risk in the next 10-15 years. Thinking this will happen in 1 years time is myopic in my opinion.
Just use a state of the art LLM to write actual code. Not just a PoC or an MVP, actual production ready code on an actual code base.
It’s nowhere close to being useful, let alone replacing developers. I agree with another comment that LLMs don’t cut it, another breakthrough is necessary.
We will see, maybe models do get good enough but I think we are underestimating these last few percent of improvement.
The problem case is the somewhat odd scenario where there is an AI that's excellent at software dev, but not most other work, and we all have to go off and learn some other trade.
AI is obviously not good enough to replace programmers today. But I'm worried that it will get much better at real-world programming tasks within years or months. If you follow AI closely, how can you be dismissive of this threat? OpenAI will probably release a reasoning-based software engineering agent this year.
We have a system that is similar to top humans at competitive programming. This wasn't true 1 year ago. Who knows what will happen in 1 year.