𝗧𝗵𝗲 𝗛𝗶𝗱𝗱𝗲𝗻 𝗥𝗶𝘀𝗸𝘀 𝗼𝗳 𝗢𝘃𝗲𝗿-𝗥𝗲𝗹𝘆𝗶𝗻𝗴 𝗼𝗻 𝗔𝗜 𝗶𝗻 𝗖𝗼𝗱𝗶𝗻𝗴

In today’s fast-paced tech world, AI-powered tools have become incredible assets for developers. They help us complete lines, offer suggestions, and even debug parts of our code. I’ll admit, I was thrilled the first time I used AI for coding. It was like having a helpful co-pilot that made everything quicker and smoother. But as I kept working with these tools, I started noticing a downside: relying too much on AI came with its own set of challenges, some of which could actually hold me back in the long run.

𝟭. 𝗧𝗵𝗲 𝗜𝗹𝗹𝘂𝘀𝗶𝗼𝗻 𝗼𝗳 𝗠𝗮𝘀𝘁𝗲𝗿𝘆

Using AI can sometimes make us feel like coding experts, when, in reality, we’re leaning more on its suggestions than our own understanding. I remember when I first started using AI-assisted coding; I’d see a line of code pop up, and I’d accept it right away, trusting the tool more than myself. But over time, I realized that I didn’t fully understand what I was doing, especially when it came to more complex logic. I learned that it’s essential to question why AI suggests certain solutions, to dig into the "why" behind every recommendation, and to make sure I’m genuinely learning from the process.

𝟮. 𝗦𝘂𝗽𝗲𝗿𝗳𝗶𝗰𝗶𝗮𝗹 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴

One of the best parts of coding is the challenge of solving problems, and the lessons you learn along the way. When I relied too much on AI, I noticed that I was skipping this crucial learning phase. Instead of grappling with the logic and figuring things out myself, I was letting AI fill in the blanks. It was only when I stopped to break down each suggestion and tried to write parts of the code manually that I felt my understanding deepen. Relying solely on AI made it easy to gloss over concepts that I really needed to master on my own.

𝟯. 𝗗𝗲𝗯𝘂𝗴𝗴𝗶𝗻𝗴 𝗗𝗶𝗳𝗳𝗶𝗰𝘂𝗹𝘁𝗶𝗲𝘀

This one hit home hard. Early on, I’d let AI take over too much, and when something broke, I was completely lost. Without truly knowing the ins and outs of my code, debugging became a nightmare. AI can’t teach you how to troubleshoot effectively. It can point things out, but it doesn’t replace the need for your own problem-solving skills. Debugging is a skill you only sharpen by going through the process yourself. I’ve learned now to keep AI suggestions to a minimum during debugging so I can actively work through each error and build my understanding.

In my journey, I’ve come to see AI as a powerful tool that can enhance our skills, but only if we use it wisely. By balancing AI assistance with our own problem-solving and critical thinking, we can ensure we’re not just writing code. We’re understanding it.