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I am a computer engineer that has experience in backend development. I have worked with Python, Elixir, NodeJS, learned C and Java at university. I also have some minor experience with frontend (Angular and React). It is clear to me that I prefer backend development. On the other hand, I did a master's degree, researching in Machine Learning and have even worked as a Data Scientist for some months. But then I figured I like better the software part rather than the data/statistics part of it, so I am planning on moving to Machine Learning Engineer. All those name, though, have different meaning for each company, I believe. I currently work developing AB testing tools for a large company. That is just so you know a bit about myself in order to help with giving an answer. The question is, considering nobody has a crystal ball and we don't even have an idea of what tools await us, what should I focus on? Of course, according to your opinion and experience.

I am taking a Backend Developer Certificate from Meta (FB) and will also get an AWS Certified Developer - Associate Certification. Besides that, I have been developing my people-and-managing skills, helped hire people and also help people learn.

What other advices would you give me?

DSchlingel
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I believe that the so called "code monkeys" will be replaced the first in programming. Meaning "A computer programmer who is not involved in any aspect of conceptual or design work, but simply writes code to specifications given". Then, the testers may be replaced also soon. As these systems get better, they will understand the software better and generate the tests. However, there will still be a need for good testers that are able to create tests that reveal trick bugs. However, these are few compared to the majority. Finally, coding at some point may just become obsolete.

I think anything that does not involve too much creativity will be automated very soon by these systems. Personally, I think doing research will continue for a long time. These systems are not that creative yet and they need a lot of skills to come with a problem to research, read the relevant literature, develop a solution and test it accordingly. Like, inventing new algorithms, new neural networks architectures, etc. They may be good at this point to come with a solution given a very restrictive problem but they can't do the whole process yet. But also, at some point they will be able to do it.

So, I believe it is just a matter of time until they can do everything we can. It only matters how long you want to be relevant, and this depends heavily on how much creativity you need for the job. "Low creativity"=="soon to be replaced by machines". "High creativity"=="to be replaced by machines at a later date"

What I said here refers mostly to the white-collar jobs. For blue-collar jobs, the situation is different and they may not become obsolete soon. However, this can also change rapidly if the progress in robotics suddenly starts to accelerate.

Otniel-Bogdan Mercea
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