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.
Pair programming/writing/creating is exactly how AI is meant to be used. It is an augmentor not a replacement for human competence. The person using it still has to do the thinking, qc, and directing, not take the first output as final.
And always with skepticism!
A couple other cool things I’ve seen experts do:
The first: finding bugs which, considering the scarcity of humans capable of bugfinding doesn’t seem so bad in our weeks with finite hours.
Next, really tedious work that experts do know how to do, but simply wouldn’t prioritize because they have lives. A big one seems to be reverse engineering, like to give new life to ancient hardware. “I connected <ewastey thing> over USB at <IP>, give me control.”
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.
My coworkers use Claude like an actual brain subscription, and I have started to write off everything they say as if it came straight from the AI. They have gained so much unearned confidence about shit they have no idea about, and have even argued with the development team about it.
I got into an argument about how in band and out of band DTMF work with one of them for a solid half hour before they finally admitted they didn’t actually know but were going off what claude said.
I wanted to punch them for wasting everyone’s time. If you don’t understand stop answering definitively like you’re the expert.
Some customers have switched to using AI emails too. Customers that used to ask extremely low level questions will now submit a 2 page long email with action items and explinations about why our product does X, Y, Z, and I have to read it twice to figure out their problem isn’t even in the action items because the AI hyper focused on the wrong thing.
Like ok thanks you dumped the entire app log into Claude and asked it “why no work” and Claude read an error message that’s benign and now the customer is demanding fixes for something that is not and never has been a problem and won’t actually solve the root issue.
But just think of those billable hours
Well, yeah…
Most of the time it doesn’t work, rarely it does.
Intermittent rewards are what we’re wired for. That’s why random rewards/acknowledgment tickle our brains more than standard rewards we know are coming.
That’s the reason there’s such a big push “to just try it”.
It’s the same strategy the first crack dealers used
It feels so weird to read lemmy, as if I’m living in a different reality. To me, most of the time an agent can oneshot a ticket (if it has a good, non-vague description) or at least do 80-90% that can be fixed with several changes or prompts, and only odd tasks need more manual investigations than that.
Surely you still need a dev oversight and someone needs to do tech plans & lead the projects, but that’s not like anything people experience here.
For the little stuff sure. Most of us are the ones that handle the odd tasks.
