It's a Dilbert world !

I just used ai to do three things that were a bit outside my skill and comfort zone. I’m pretty sure there are lots of people using it to good effect. Actually two things that were totally outside and one thing that is well within, but would have taken me eight hours and with me directing it took the ai about 12 min.

Most software engineers I know use some amount of ai assistance in coding.

Pretends is a pretty strong word here. A lot of people actually use it to help them do their work.

Didn’t read the article, and I’m an engineer who is using too many genai tools personally and professionally, but the title spoke to me: I am 100% pretending that my professional artifacts came from genai tools.

Part of it is that “what good looks like” - from leadership - looks a certain different way right now, thanks to LLMs. The other part is that knowing isn’t enough in a large org, you have to show.

We are embracing this SO HARD, I need my communication to look like this, and most importantly my teams communication needs to implicitly show that we are bought in (to accompany the explicit proof, measured in token kpis - not kidding).

Not in the US, but I exaggerate my use of AI to the CEO because he has fully taken on board the idea that AI can do everything, except presumably his own job.

I do use AI, but I make out it's a bigger part of my workflow than it is to appease him.

I'm trying to figure out ways to placate the boss by fitting AI into the edges of my workflow.

"Look at these commits and do a review" to find stupid stuff like forgotten exception throws or nulls. Or "Critique this documentation for a different audience"

I don't want to get into the "let the machine write the code" phase because that's the task I enjoy most, and it swaps my efforts into review, which I'm bluntly less confident about (having to follow and second-guess an architecture without being "there" when it was evolved increases the chances I'll miss stuff)

The stuff that AI demos well at-- "refactor 5,000 lines of code", "build a new client from ground level" are simply not what my team works on; we end up doing things where building a prompt to actually make the change we want-- and only the change we want-- takes longer than writing the code itself. 80% of the time is the debugging and planning.

Some use AI detection to be sure that you're not cheating. Others use AI detection to make sure you're doing your job. "This is terrible, bring it back to me when it's slop!"