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?
Because that command might also give someone else access to your computer along the way. So your tool seems to work, but your computer is owned.
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.
These non-programmers probably shouldnt use computers at all, right, since they don't understand them?
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.
The real answer is somewhere in the middle and is probably a mix of traditional AV/EDR and AI QA judges that mitigate risk of running more or less random arbitrary code and auto approve based on configured detection rules and your personal risk tolerance. Would it suck to stick an EDR sensor in every code execution environment spun up for an agent to run a python script… yes. It would also suck if you were responsible for hacking a company without knowing about it because you didn’t watch what your AI was doing