Recently, I found myself reflecting on how much artificial intelligence has influenced my life, especially as a software developer. It feels like yesterday when Google was my main lifeline. Whenever I encountered a coding issue, I'd type my questions into the search bar and then spend time carefully picking apart the solutions. This process wasn't just about finding quick fixes—it actually helped me deepen my understanding of programming concepts.
But then AI entered the picture, and the landscape shifted dramatically. At first, the convenience of AI thrilled me. With just a simple prompt, AI could generate complex database schemas, elegant code snippets, and even solve tricky errors instantly. It felt like magic.
Slowly, though, I began noticing a concerning change in myself. As solutions became easier to obtain, my brain became lazier. Instead of carefully examining and understanding each piece of code, I started to blindly trust AI-generated responses. If something broke, instead of diving deeper into the issue, I'd simply toss the error message back to AI, hoping it would sort everything out for me.
This growing dependency made me realize something critical—I was losing my creativity and critical thinking skills. The intuition and problem-solving skills I once prided myself on were slipping away. Coding started to feel mechanical rather than inspiring.
Interestingly, this experience reminded me of how new medications are often introduced into society. Initially meant to help and heal, a drug becomes problematic when overused or misused because it's too easily accessible. Similarly, AI itself isn't inherently harmful. It's our excessive dependence on it that creates the real problem.
This also made me think about another familiar scenario—the stock market. Imagine someone you trust gives you a tip that a certain stock will rise tomorrow. Excited, you buy it immediately. When the stock indeed rises, your excitement peaks, and you become increasingly dependent on your advisor for every next step. Rather than making informed decisions yourself, you continuously seek their validation and guidance, becoming completely incapacitated by dependency. This scenario mirrors how I started to feel with AI-generated solutions—dependent, unsure, and less confident in my abilities.
During this time, I stumbled upon an interesting psychological concept known as the Dunning-Kruger effect. This phenomenon describes how we often experience high confidence when we first start learning something new. Soon after, though, we hit a reality check—a phase called the "valley of despair"—when we realize we actually know very little. AI had rapidly taken me straight into this valley. My initial high confidence turned into a sense of inadequacy and frustration.
Thankfully, becoming aware of this issue was the first step towards a solution. To overcome my over-reliance on AI, I adopted a practice I like to call "mindful coding with AI". Rather than using AI to directly provide solutions, I began forcing myself to write out my own solutions first. Whether it was planning a database schema or figuring out a complicated algorithm, I gave it my best shot before turning to AI.
Only after presenting my ideas would I then use AI, but now as a mentor rather than a solution-provider. AI could critique my work, suggest improvements, and help me identify mistakes. This new interactive and mindful approach transformed my relationship with AI from dependency into collaboration.
Since adopting this practice, I've noticed a remarkable change. I'm actively learning again, my confidence has grown, and coding is once more exciting and intellectually stimulating.
In the end, AI can indeed be a "drug"—but only if we misuse it. When approached mindfully, AI becomes the most valuable partner a coder could hope for, enhancing creativity and productivity rather than replacing them.