That’s because it doesn’t know what it’s saying. It’s just blathering out each word as what it estimates to be the likely next word given past examples in its training data. It’s a statistics calculator. It’s marginally better than just smashing the auto fill on your cell repeatedly. It’s literally dumber than a parrot.
Yeah, but not when it comes to understanding human speech. There’s a reason that repeating words without really understanding them is called parroting. Gray parrots are the smartest and some can actually understand language a little bit, making them smarter than chat, which is just high tech guessing without comprehension
It’s even worse when AI soaks up some project whose APIs are constantly changing. Try using AI to code against jetty for example and you’ll be weeping.
Oh man, I feel this. A couple of times I’ve had to field questions about some REST API I support and they ask why they get errors when they supply a specific attribute. Now that attribute never existed, not in our code, not in our documentation, we never thought of it. So I say “Well, that attribute is invalid, I’m not sure where you saw to do that”. They get insistent that the code is generated by a very good LLM, so we must be missing something…
All AIs are the same. They’re just scraping content from GitHub, stackoverflow etc with a bunch of guardrails slapped on to spew out sentences that conform to their training data but there is no intelligence. They’re super handy for basic code snippets but anyone using them anything remotely complex or nuanced will regret it.
One of my mates generated an entire website using Gemini. It was a React web app that tracks inventory for trading card dealers. It actually did come out functional and well-polished. That being said, the AI really struggled with several aspects of the project that humans would not:
It left database secrets in the code
The design of the website meant that it was impossible to operate securely
The quality of the code itself was hot garbage—unreadable and undocumented nonsense that somehow still worked
It did not break the code into multiple files. It piled everything into a single file
I’ve used agents for implementing entire APIs and front-ends from the ground up with my own customizations and nuances.
I will say that, for my pedantic needs, it typically only gets about 80-90% of the way there so I still have to put fingers to code, but it definitely saves a boat load of time in those instances.
I don’t use it for coding. I use it sparingly really, but want to learn to use it more efficiently. Are there any areas in which you think it excels? Are there others that you’d recommend instead?
ChatGPT has been, hands down, the worst AI coding assistant I’ve ever used.
It regularly suggests code that doesn’t compile or isn’t even for the language.
It generally suggests AC of code that is just a copy of the lines I just wrote.
Sometimes it likes to suggest setting the same property like 5 times.
It is absolute garbage and I do not recommend it to anyone.
That’s because it doesn’t know what it’s saying. It’s just blathering out each word as what it estimates to be the likely next word given past examples in its training data. It’s a statistics calculator. It’s marginally better than just smashing the auto fill on your cell repeatedly. It’s literally dumber than a parrot.
Parrots are actually intelligent though.
Yeah, but not when it comes to understanding human speech. There’s a reason that repeating words without really understanding them is called parroting. Gray parrots are the smartest and some can actually understand language a little bit, making them smarter than chat, which is just high tech guessing without comprehension
my favorite thing is to constantly be implementing libraries that don’t exist
You’re right. That library was removed in ToolName [PriorVersion]. Please try this instead.
*makes up entirely new fictitious library name*
It’s even worse when AI soaks up some project whose APIs are constantly changing. Try using AI to code against jetty for example and you’ll be weeping.
Oh man, I feel this. A couple of times I’ve had to field questions about some REST API I support and they ask why they get errors when they supply a specific attribute. Now that attribute never existed, not in our code, not in our documentation, we never thought of it. So I say “Well, that attribute is invalid, I’m not sure where you saw to do that”. They get insistent that the code is generated by a very good LLM, so we must be missing something…
All AIs are the same. They’re just scraping content from GitHub, stackoverflow etc with a bunch of guardrails slapped on to spew out sentences that conform to their training data but there is no intelligence. They’re super handy for basic code snippets but anyone using them anything remotely complex or nuanced will regret it.
One of my mates generated an entire website using Gemini. It was a React web app that tracks inventory for trading card dealers. It actually did come out functional and well-polished. That being said, the AI really struggled with several aspects of the project that humans would not:
I’ve used agents for implementing entire APIs and front-ends from the ground up with my own customizations and nuances.
I will say that, for my pedantic needs, it typically only gets about 80-90% of the way there so I still have to put fingers to code, but it definitely saves a boat load of time in those instances.
I’ve had success with splitting a function into 2 and planning out an overview, though that’s more like talking to myself
I wouldn’t use it to generate stuff though
I don’t use it for coding. I use it sparingly really, but want to learn to use it more efficiently. Are there any areas in which you think it excels? Are there others that you’d recommend instead?
Use Gemini (2.5) or Claude (3.7 and up). OpenAI is a shitshow