Tag Archives: Mistakes

[ad_1] Had I planned it out ahead of time, I would’ve went with the tabbed layout that I eventually used, right from the beginning. The overall process would have gone much smoother. Here’s what I think works better Once you decide on what you want your plugin to do on a broad-level, find existing plugins that do the same thing or that have some overlap. Install them on a dummy site using TasteWP and use them. But don’t just use them like a regular user. Use them like a UX researcher would use them. Make careful notes on how different things work. What do you like? What would you do different? After you perform this plugin testing, organize your notes. Then put together a detailed description of your prototype. Ask yourself how users will interact with it. Will they use shortcodes? Will they add extra blocks inside the block editor? Will there be a settings area on the back end? Cover all your bases. Consider using wireframes to visually map out how users will navigate their way around your plugin. You can get free wireframes over at Figma. When you finish the above, use your detailed description and possibly any wireframes you create, to give your first prompt to ChatGPT. My recommendation for the prompt is to start small and gradually build. This way you can more easily isolate and fix any bugs that come up. Using my plugin as an example, if I was to do it all over again, I’d first give GPT a broad overview of what I want to do. I’d also mention the tools and scripts I want to use. Then I would begin building only the first effect along with the corresponding area for it on the back end. I’d test it to make sure it works. If all was well, I’d add the next effect, and so on. Mistake #2: Ignored WordPress coding standards at the beginning Another big mistake I made was that I didn’t realize how big of a gap there is between simply building a plugin that works and building a plugin that is worthy of submission to the WordPress repository. You might be surprised, but going from zero to functioning plugin is much easier and faster than going from functioning plugin to well-coded plugin. To put this in real-number terms: It only took me about two or three days to build a functioning plugin, but it took me another seven weeks of work before I got it to a point where I was able to submit it to the WordPress repository for consideration. Even if your ultimate goal is not to submit your plugin and you only want it for yourself or a client’s website, you should still follow coding best practices. This will ensure that your plugin doesn’t cause other things to break on your site and doesn’t put an unnecessary strain on your site’s resources. Here’s what I think works better Make sure you tell ChatGPT (or Claude) right from the beginning that whatever code it generates should follow WordPress coding standards. If you’re planning on submitting your plugin to the WordPress repository, then for good measure, also add that any indentations should be done using tabs and not spaces. GPT has a tendency to default to spaces, but this goes against the coding standards. If you don’t nip it in the bud right from the get go, then you’ll have to deal with it later when you do your linting. Might as well do it correctly from the start. Mistake #3: Allowed GPT to constantly regenerate entire code files One thing you might be tempted to do when you have very little experience working with code is to ask ChatGPT to regenerate entire code files when you’re debugging. I was guilty of this, until I realized it was getting me nowhere. It’s not necessarily an issue if you’re dealing with a relatively small JavaScript file that’s 50 to a 100 lines long. However, as your plugin gets more complex and your main PHP file starts growing considerably, then it becomes highly problematic. For one, it takes GPT some time to generate that code. For example, let’s say you have a bug in a file that contains 800 lines of code. Now imagine the actual problem is found on only one of those 800 lines. Does it make sense to sit in front of your monitor for five minutes, watching GPT regenerate 799 lines that it doesn’t need to? No, it doesn’t. And here’s the other problem: As the length of your code grows, ChatGPT’s memory worsens. What ends up happening if you allow it to regenerate very long sections of code, is that it won’t only tweak the problematic lines you’re trying to debug, but it’ll also accidentally change other lines. So now you might fix the error you wanted to fix, but you’ll be stuck with some new error(s). If you continue going about it the same way, it will leave you in an endless loop of debugging. You’ll feel like you’re trapped in the Matrix. Neo won’t be coming to save you though. You must save yourself. Here’s what I think works better When you’re debugging, make sure to include very specific instructions to ChatGPT in your prompts to keep it laser-focused. After some trial and error, I found that telling it to do the following worked well: Please do not regenerate the entire file for me. Analyze and isolate the specific lines of code that you believe are causing the problem and show them to me. Explain what specifically about those lines you think might be the issue. Then explain how you are going to change the lines and what you expect the outcome to be as a result of the changes. Finally, please give me the updated lines in a code snippet so I can copy and paste them. Mistake #4: Used plain vanilla CSS instead of BEM CSS If there’s

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