I know there are good uses of LLMs out there. I do. But.

The current fever pitch mandates from above seem to want it applied liberally, and pushing back against that is so discouraging and often career-limiting as to wear the fabric of one's psyche threadbare. With all the obvious problems being pointed out to people, there are just as many workarounds; and these workarounds, as is often revealed shortly thereafter, have their own problems, which beget new solutions, ad infinitum.

At some point it genuinely seems like all this work is for the sake of the machine itself. I suppose that is true: The real goal has become obscured at so many firms today, that all that remains is the LLM. Are the people betting the farm and helping implement the visions of those who have done so guaranteed a soft exit to cushion them from the consequences, or is rationality really being discarded altogether?

Sure, sound engineering principles can help work around these problems, but what efficiency is truly gained, in terms of cognitive load, developer time, money, or finite resources? Or were those ever an earnest concern?

In my opinion you are just wrong.

It’s an absolute game changer, and it can now multiply your productivity fivefold if it’s a solo greenfield project.

Maybe half a year ago it was as you said. You had to wait for the agent to finish, you had to review carefully, and often the result was not that great. You did not save a lot of time.

Now I can spin up 3+ parallel conversations in Codex, each in a git worktree. My work is mainly QA testing the features, refining the behavior, and sometimes making architectural decisions.

The results are now undeniable. In the past I could not have developed a product of that scope in my free time.

That is what is possible today. I suspect many engineers have not yet tried things that became feasible over the last months. Like parallel agents, resolving merge conflicts, separating out functionality from a large branch into proper PRs.

There's two sides to the AI mandates.

The degenerate side is clueless upper management and fad-driven engineering. We have talked extensively about this.

There is a more rational side to it that I've seen in my org: some engineers absolutely refuse to use AI and as a consequence they are now, clearly and objectively, much less productive than other engineers. The thing is, you still need to learn how to use the tool, so a nontrivial percentage of obstinate engineers need to be driven to use this in the same way that some developers have refused to use Docker or k8s or whatever.