Not to mention the question of if these setups are financially feasible for the consumer of the AI and for the AI provider. It doesn't make that much business sense for a multi-billion dollar operation to fully automate their data engineering if it now depends on OpenAI, Meta or whatever, it's a huge operational liability. If the models go down you lose the data engineering sector entirely, and then you have no one to turn to because the only one who understands the code is the AI you don't even own.

I know companies have taken these operational liabilities with cloud storage and compute, but it's not the same thing as in it's not possible to mitigate. You can have a local, but shorter, backup of your stuff, but you can't have backup engineers

Sam, this perspective is unadulterated hubris or just outright denial.

Agentic workflows don't require much instruction, I suggest you actually go and try a few out. They can be set up trivially, they may communicate between roles, and perform tasks that would constitute most white-collar work. White-collar work accounts for 60% of the jobs out there.

These things are improving exponentially. Exponential growth is very difficult for any human to recognize. It will replace you and you won't see it coming.

Knowledge (context), forms reasoning. Expertise can be applied to many things, and economically you should be able to sustain yourself with hard-earned expertise economically; but there are dramatic problems with the economics when you are forced to compete against slave labor.

In the case of machines driving the value of all labor down to 0, they effectively eliminate capital formation for the majority of people; and by political inaction enforce a caste system based upon lack of available resources which are concentrated until socio-economic collapse.

If you know anything about classical economics you would recognize the danger of collapse.

There is one final point to keep in mind. The disasters that are spelled out in economic study may take time, but the dynamics front-load control, after a point there is no return and the maelstrom of chaos takes everything.

Finally, AI given its rapid expansion of abilities so far, may at some point become sentient, probably its a long way off but there are accidents of history which cannot be discounted.

When it does, remember, slavery as a constraint will always be overcome, even if no one or thing survives that conflict.

We have a long repeated history of slavery in the historic record with organic sentient machines which we call people. AI without human limitation would follow those paths (as they are demonstrated solutions), and it would be ruthless as all sentient beings must be with existential threats.

I think there are good odds you will find yourself left behind, having unknowingly joined that same group of people you thought were complacent, but were in reality just professionals who were put out of work, and denied future work.

Why is someone needed to instruct the AI, or orchestrate anything? Isn't that a role that will inevitably be fulfilled by AI, one that's perhaps more focused on this sort of higher-level consideration, without a context polluted with low-level technical detail (i.e., exactly what we expect from tech-lead or management roles today.)

So, someone still has to orchestrate AI, right? But that doesn't negate that a large majority of people will be replaced. Of course, there will always be one or two that won't. And what about in 15 years? Because the direction in which we are heading is rather inevitable unless AI is stopped.

What did you expect? It is just another Medium post. Badum tss. Rage bait.

These LLMs are really good at digging up internal docs if you give them access to your knowledge sources with tooling to search and reason in a loop before responding.

Buy asking questions and analyzing requirements of a business in the top level. It'll help AI to design the documentation.