Why Does AI-Generated Code Seem Off Despite Looking Fine?

One effective approach I've found is to create a detailed architecture document, like a VISION.md. It helps the AI understand the overall context before generating code. If the output isn’t satisfactory, I give it feedback to improve. This method has increased the accuracy of the code significantly.

The issue you’re experiencing isn’t uncommon. AI-generated code might look good, but it often lacks context and can confuse beginners with its decision-making. I recently dealt with several hours fixing up code generated for a marketing site. It’s great to give AI specific guidelines, but, for now, expect to do a lot of post-processing.

Remember, AI is just a fancy autocomplete. It can produce code that looks correct but isn’t necessarily functional or efficient. The best use for it is explaining code logic or generating basic setups. It's risky to rely on it for complex coding tasks—learn the basics first!

As a beginner, using AI can be challenging. If you provide vague instructions, it tends to produce poor-quality code. Even with detailed prompts, you'll often end up with code that reflects your own mistakes. Just be cautious; while AI can offer a decent starting point, be prepared for a lot of cleanup afterward.

If you're just starting out, focus on learning the fundamentals before leaning on AI for coding. Tutorials and practice will help you understand how to interpret and create code. Once you do, you'll likely find AI tools more helpful as you’ll be better at spotting errors and understanding suggestions.