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by jocoda
446 days ago
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My, very limited experience with LLM assisted coding is that it depends...
For basic frameworks done in something like Python it is very good, but not perfect, yet. But the iteration cycle to get to where you want to be is still faster than doing the whole job manually and I see this as a big win. For more esoteric fast changing languages/frameworks it has me chasing my tail in a chain of code updates where each fix breaks something in the n-1th, or n-2th version. Sometimes it's deprecated code, or it halucinates functions that would be valid if your were using a a different language of framework. And sometimes simple coding errors. But it will get better, a lot better. The main benefit is that it will let a invested non programmer client build a functional framework prototype and then combine that with a list missing features that a more skilled programmer can flesh out to a first cut solution. For the first time we 'might' get better requirements with an actual working model instead of having the implementor doing most of the requirements as a first pass from a high level hand wavy requirement. I think we're going to see some amazing tools for this. What I don't see it doing is creating original algorithms to solve things being done for the first time. |
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I see statements like this a lot when talking about AI in general. People seem to think it is a foregone conclusion that no limit to LLM model improvement and capability exists. What causes you to believe this and what evidence do you have to back it up?