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arkuw t1_iyyg5kt wrote

Reply to comment by SatoriSlu in OpenAI ChatGPT [R] by Sea-Photo5230

I generally think of "devops" as a dying career. Yes the "cloud" created a lot of need for people who understand system administration and can apply it to swarms of computers (aka the cloud).

But cloud vendors realize that the next value add for them is to start working towards eliminating the need for "devops". Thus new platforms are emerging that stitch together common compute, db, storage and messaging components in a way that is palatable to most cloud customers thus reducing greatly the need for a "devops" team at customer companies.

So a "devops" career strikes me as a perilous career, AI takeover or not.

In the context of this thread howeveer, I'm thinking that the LLMs are more likely to impact programmers first. However it's the cloud vendors themselves that are working hard at eliminating jobs for "devops" people. That's the whole goal of "serverless" after all.

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SatoriSlu t1_izsvffi wrote

You may be right. Although I think there's a shift to a more defined role in 'platform engineering'. In my experience, the business users are not programmers, but they have the domain knowledge, so they need guidance on what technologies to use and how to stitch them together.

I think there will be a shift to understanding which technologies to stitch together, proper configuration of those platforms, and securing them. The so called, providing 'golden paths' for business users to ingest philosophy.

But, anyway, I think I'm gonna shift to learn more 'analysis' like roles. I believe that's where humans will ultimately move towards, feeding these systems data, asking the right questions, learning how to prompt them, visualize the output, and analyze more deeply.

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balder1991 t1_j04b2f5 wrote

I don’t think that IT jobs are going away anytime soon because despite we create things to make our work easier, there’s always a performance cost involved. You can’t add layers forever to push the complexity under the carpet. At some point, when something breaks, we need to be able to understand it and fix it, even if there is an AI helping us debug things faster.

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