I recall hearing similar sentiments from linux sysadmins regarding cloud infrastructure. In many respects they were and continue to be correct. In other respects, the world doesn’t care about the loss in understanding as long as things work “well enough” for the cogs of society to keep turning.
For those who do care (and have the aptitude) to understand things deeper there is always work to be had when “well enough” stops being good enough and someone has to unravel the “RDS queries are taking too long” problems that crop up as a result.
I review and test the end product, not every tiny step along the way. If the LLM uses some command line tools I have never heard of to create a model I can verify, why should I learn a tool that is completely irrelevant to my core expertise?
In terms of engineering software, you care the cost. An intelligent agent may try to read unnecessary files and it's time to stop it to save tokens and avoid polluting the context.
It is a broader debate about agentic AI, and whether one should relinquish control to the tool rather than aim for full understanding of every action taken.
The people arguing for a hands-on, fully in control approach are losing ground by the week, in my opinion.
These non-programmers probably shouldnt use computers at all, right, since they don't understand them?