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.

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.

Considering the vast amounts of knowledge it has at its disposal, I can only conclude that it’s not very smart at applying it. A person with a fraction of that knowledge will produce better results.

So it has more access to information, but the results are poor compared to a person.

The important thing to remember is that it actually has zero access to information, because that’s not how LLMs work.

At their core, they’re vector databases, and they’re trying to probabilistically come up with the next most likely token in a stream of tokens found in the DB. You can manipulate the stream by injecting text such as the content of existing files (which becomes more tokens) into the stream, but it never actually understands any of it.

That’s why hallucinations are inherently unavoidable. It’s really all just hallucinations. It’s just that you can sometimes get useful text from their hallucinations if they happen to comport with reality.

Well, vector fields are information. But they have no understanding. The number 1 might be followed by 2 in 99.999% of cases, but it has no function to explain why, or to contextualize a scenario where that might be wrong.