Hard to believe. I don't know any programmer who uses ChatGPT on a regular basis for programming. How can anyone rely on a thing that frequently isn't available because high load, and takes tens of seconds to generate a full answer. Secondly, for most of the programming work, to be useful, it has to be able to understand the query but also the existing codebase—"This is my codebase. What do I need to do to paginate the users table?".<p>Would love to hear real-world programming examples of something that would be faster done with ChatGPT vs Google/Github Search. What are they?
I dunno, this makes me feel weird. So far I've tried AI for programming assistance but every time I do, the results are disappointing and I give up. Yet I hear from others that it's made a huge difference and been a massive boost to their productivity. I don't know how to reconcile these two very different experiences. I worry that I might be getting old and will be left behind by not understanding how to master these new tools.<p>Specifically, I have a colleague I respect a lot. He is an excellent programmer. He now routinely asks ChatGPT for things and claims it's a big help. Yesterday I was wondering out loud what the difference was between two very similarly named properties in a config file, and he immediately logged on to ChatGPT and asked it. I read the answer and became suspicious because the explanation was what you'd <i>expect</i> the difference to be given the different names, but it didn't make any sense when you thought about it carefully. I typed a similar query into Google and the first result was a detailed and correct Stack Overflow answer. Now I'm quietly wondering about the other cases where he used ChatGPT to help him write code. When I tried ChatGPT to get library recommendations per tasks, it would often recommend libraries that sounded like they should exist but didn't.<p>Other people say they use Copilot and it's a huge boost. I tried it when it first came out. It kept suggesting huge blocks of code that were just nonsense, in a very irritating over-enthusiastic-girlfriend-meme sort of way. I found it was slower to try and work with Copilot constantly checking its answers than it was to just rely on the IDE autocomplete and type system (which are quite good in the language I'm using). Also I found that carefully reviewing its suggestions was somehow more tiring than just writing the code myself.<p>Finally, when I look at the bugs and things I've had to do lately, it's hard to imagine (current gen) AI helping. Everything is a bunch of small changes all over the codebase, often quite subtle and in response to complicated bug reports. Who are these programmers who are blasting out boilerplate all day where AI never makes mistakes?
I don’t believe this story and I’d encourage anyone who thinks it’s plausible to recalibrate. 25% of the team has forgotten how they did their job 2 months ago? Come on. Either the story is exaggerated for clicks or the portfolio company was making excuses for why they didn’t hit some deadline.
If you read further on in the thread:<p>> "They can still work and the company does not rely on them to generate revenue. It is just from an IC tooling perspective in a short amount of time, they have become dependent on it. They can still go back to less productive ways but just a usage behavior observation"
I love how some tech-early-adapter-visionary-influencers make even bigger claims in this thread:<p>> I think for some it’s already as critical as wifi.<p>Personally I would like to add that for me ChatGPT is as critical as running water and sewage.
Maybe their work involves posting ChatGPT-generated memes to each other in code review.<p>If that were the case, I would turn off ChatGPT M-Th at 6 pm and every Friday at 4.