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Not surprising at all. I throw a wall of code at GPT-4, write a paragraph of what i want it to do (I couldn't spend the time to figure out a good solution), and within a minute I had a great functioning solution perfectly integrated into my existing code.

The surprising thing is not that it was able to code a good solution, it's that it was able to understand the specifications of how i wanted it to work and how it should be integrated into the existing code.

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Does it compile ? (the code generated)

In my experience with ChatGPT-4, I'll get a full 2-300 line class, with maybe 1-2 compilation errors (often a missing import or invalid function invocation). In most cases, I can copy the compilation error back into the chat, GPT will apologize, fix it, and it'll run correctly the second time.

It's obvious that this will be faster and more effective once a GPT4-class model is tightly integrated into the run-compile-test loop.

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