80% of developers find AI coding more addictive than helpful

A new Coddy Developer Survey found that four in five developers, 80%, say their use of AI has felt more like a dependence than an advantage.

www.zdnet.com/article/80-of-developers-find-ai-coding-more-addictive-than-helpful/

I had this experience once. We have a ChatGPT license where I work, and I asked it to configure a switch that I wasn’t familiar with. I simply described in words what network architecture I wanted and it did it! It even made some nice-looking documentation.

But, then I tried the new configs, and they didn’t work. It turns out there were some key syntax things it got wrong. And the documentation was wrong on top of that, with incorrect diagrams, and when I asked it to fix it it made different errors I the diagrams in different places. On balance, I still saved some time over reading all the manuals and figuring out the syntaxes myself, but only because I made my own documentation with the results that worked. If I had trusted the AI I would be sunk.

I’ve concluded that AI gives the illusion of competence, like a overly confident new manager. This can be very attractive to a less experienced person. But it’s really guessing, just like we all are. It can just guess after actually “reading” all the manuals. I haven’t used AI to write anything more than simple configurations and helper scripts. If I did want to use AI for more it would be in more of a pair-programming context. I might have a window open where I describe some things and ask for analysis, but I wouldn’t just run anything it does blindly.

But it’s really guessing, just like we all are.

Beyond the moralistic objections I have to LLMs, I have serious issues with being fed confidently incorrect answers. I’ve had my share of configuration hell and I’m not above throwing code at the wall to see what sticks, but at least I have the good sense to drop a comment or mention in my commit that “hey, there’s a chance this isn’t right and could cause problems”.

I have serious issues with being fed confidently incorrect answers.

Except I have plenty of experience dealing with this from humans. (Mainly from the aforementioned new managers, because being wrong with confidence seems to be a key trait to get promoted.) It’s been my experience that when you tell an AI “I just tried that and it didn’t work”, it will accept that more readily than a human would.

Every bit of AI-generated code that I use, even in the smallest and most meaningless context, has to pass my own review first. I have to understand every line, and if I don’t I will ask the bot to explain what it did. By the time I am done with it, I can stand behind it just as if I wrote it all myself. I might note that I got AI help, but if my name is on the commit I will not pass the buck on any errors.

I don’t trust A.I. code at all. If I ever do use it, I use it as a research tool like “please google for me how to do this one obscure thing because IDK what search query to use”; then I type out it’s output manually. Usually as I do so, I come across some subtle error that would cause horrible problems, and fix it as I go.

I tried to use it for a mathematical algorithm once. I might as well have just written return Math.random();

This is a good thing to do if your goal is to gain a deep understanding of something.

If it’s just to get it done, I just enforce TDD on my agent and review it’s output. I don’t need to be an expert in everything (and I am very much a generalist). But if you focus on a very specific thing and only that thing, then yeah what you are doing is a great way to truly understand it. It’s slow, but it’s totally valid.