- By quade
- 7 March 2024
ChatGPT’s Code Writing Technology
Since the release of ChatGPT-4, many new features have accompanied this language model that promises to simplify and automate various tasks from creating a resume, cover leader, and coding. While these are bold claims there is still plenty of debate about its reliability. Some users have reported the language model being able to write entire plugins on WordPress, although they admit that these are relatively simple tasks.
How Reliable is ChatGPT Coding?
One thing you must understand is that no one doubts ChatGPT can write code, the issue arises with how useful it is. If properly managed, it can be an effective programmer that can simplify content. If not, then it can provide piles of useless code that you must sift through.
The biggest thing to learn is that ChatGPT cannot deliver an entire program in a single response. It is not made for that and will cause the model to overload and vomit out gibberish.
What the language model succeeds at though is creating routines or handling specific tasks. This requires the user to have some experience being a programmer as they must review the codes carefully before publishing it.
It’s important to remember that ChatGPT is smart, but not necessarily wise. It doesn’t understand nuances, context, or improvisation. This makes it unsuited for writing complex tasks that require a thorough understanding of coding.
Recommendations for Using ChatGPT Coding
To mitigate the issues listed above, many users have turned to solutions and tips that can improve the code quality of ChatGPT while ensuring that it can still help with important tasks.
The first step is always making the prompt. Before you ask the AI to do anything, you must ask yourself what you want, including the parameters and how it should be described. Since the model doesn’t always understand nuance, you must be as clear as possible.
The same is true with human programmers as well since vagueness will make the task more difficult to accomplish.
Another important thing to remember about AI is that it has access to a comprehensive library of code. Gone are the days when you must manually extra web page data in HTML tags. Since ChatGPT has a large library of information, it’s only a matter of finding the best information.
This is where you can ask the model to search for that information. Your earliest prompts can ask about which libraries they recommend and to place the code that I want. ChatGPT has 10 coding libraries with their information. Be sure to figure out which one will work best for you.
Once you have that, you can begin connecting the code. Remember that programming isn’t just writing code, it’s placing it in a way that makes sense and will serve your function.
Another important thing to remember is to focus on having ChatGPT make example code. Since it lacks imagination, it cannot usually modify or adjust existing code or does so in really troubling ways. That is why it’s better to ask the model to make an entirely new code and adjust it as you work.
This will also help you avoid issues with plagiarism as you can see if ChatGPT is just regurgitating existing code.
Can ChatGPT Replace Coders?
The biggest question on many people’s minds with ChatGPT progress is whether or not this technology is advanced enough to fully automate coding. While this technology is impressive, it is important not to overstate its capabilities.
Most coders agree that the code produced by ChatGPT is still too rudimentary to replace anyone yet. In many cases, the programmer still needs to pay close attention to what the AI writes to prevent issues like plagiarism and faulty code.
What people have agreed to is that it can be a decent assistant, handling simpler tasks, helping provide examples for programmers, and helping you visualize your code.
Here in the geniusOS team, we understand the need for a human touch in our programming service and would never dream of releasing a product we have not carefully inspected first. Our team has been drilled on the pitfalls of using AI and pays close attention to what we generate.
