>None of the things you’ve said this means match my experience using LLMs to write real, usable, viable code. It might not be the most performant or perfect code, but it’s certainly usable and most software isn’t written at Google or whatever and don’t need to support hundreds of millions of customers at scale. If it took a day instead of a month, then “the business” might decide that’s a worthy tradeoff.
It depends on your project, I seen a lot of stupidity in the AI, like in a lua project where arrays were 1 indexed it would 0 index them, somehow the c like behaviour was too strong of a force to drag the model in that direction.
For example when i test an image generator I ask it to create a photo of the front of a book store and to include no brands, labels or texts (because they always include english text and most of the time there are spelling errors), but the AIs can't make a shop without the branding/text above teh door, they are just so over trained on this concept that explicti commands can't fix it,
so the same with LLMs, they are attracted to the average most popular shit they seen in the training data, so without instructions by you or maybe by the provider behind the hidden prompts it will output outdated javascript using "var" . it will output unoptimized algorithms, and even if you used a specific variable name it will be strongly be pushed to rename it to whatever is most popular in the training data.
Yes, I can make the LLMs write soem good code but ony if I baby sit it, tell it exactly what files to read as inspiration, what features to use and what to do,
for sure I can't just paste the text in a ticket and let if free.
I also use it to review my code for bugs, it can find up to 5-% of the bugs and halucinate others that are not possible (like it would sugerate that if $x is null then something would crash and I should check for that, but the type system would already ensure $x can't be null so it really needs more training to do simple stuff... to be original and not just regurgitate the most popular things it was trained on it would need to be something not based on LLM architecture
It depends on your project, I seen a lot of stupidity in the AI, like in a lua project where arrays were 1 indexed it would 0 index them, somehow the c like behaviour was too strong of a force to drag the model in that direction.
For example when i test an image generator I ask it to create a photo of the front of a book store and to include no brands, labels or texts (because they always include english text and most of the time there are spelling errors), but the AIs can't make a shop without the branding/text above teh door, they are just so over trained on this concept that explicti commands can't fix it,
so the same with LLMs, they are attracted to the average most popular shit they seen in the training data, so without instructions by you or maybe by the provider behind the hidden prompts it will output outdated javascript using "var" . it will output unoptimized algorithms, and even if you used a specific variable name it will be strongly be pushed to rename it to whatever is most popular in the training data.
Yes, I can make the LLMs write soem good code but ony if I baby sit it, tell it exactly what files to read as inspiration, what features to use and what to do, for sure I can't just paste the text in a ticket and let if free.
I also use it to review my code for bugs, it can find up to 5-% of the bugs and halucinate others that are not possible (like it would sugerate that if $x is null then something would crash and I should check for that, but the type system would already ensure $x can't be null so it really needs more training to do simple stuff... to be original and not just regurgitate the most popular things it was trained on it would need to be something not based on LLM architecture