I don't think programming careers are/will be over. 1. The latest model is nowhere close to taking in the number of lines of code in internal projects, so will

I don't think programming careers are/will be over. 1. The latest model is nowhere close to taking in the number of lines of code in internal projects, so will be difficult to understand the design of those systems. 2. Companies developing software would be wary of sending internal code and trade secrets to the ChatGPT servers. 3. Languages, APIs, protocols, etc. evolve over time, so ChatGPT would need to keep up and handle the specific versions you are using internally. For example, Java POJOs vs record classes. Or even internal limitations like lack of runtime type information for things like embedded devices. 4. Experiments I've seen relied on external tests being in place to check the validity of the output (e.g. implementing the Promise JavaScript API), and the output had test failures that ChatGPT wasn't able to fix when told about them. -- I'd expect ChatGPT to get better at this specific example, by being fed these uses of ChatGPT in the training data, but I don't expect it to do better when shown novel specifications/requirements. ---- There are various design decisions that go into creating software that often have different trade offs. Like when implementing a compiler, you can stop on the first error, but developing a language plugin for an IDE you need to be able to recover from and handle incorrect or incomplete input. There are also things like the way you structure the code, like creating DAO/POJO/etc. wrappers for database/JSON/XML/etc. objects, or providing APIs that fit into the style of the language you are implementing them in. It would be interesting to see how ChatGPT handles something like implementing a HTML parser when given the WHATWG specs, or a keyboard driver given the keyboard specs and the driver API docs.