Danny Briskin, Quality Engineering Practice Manager
How I Got Into AI (and Why I Love Tech)
I’ve always considered myself an innovative person. My curiosity for new technology started over 25 years ago, during my university days. I was fascinated by neural networks—long before they became a trend. I explored them in pet projects and stayed engaged with their evolution.
So when modern AI tools like ChatGPT, DeepSeek, and Gemini became available, I started using them right away. Because of knowledge and experience in IT, I could clearly see their strengths and weaknesses. These tools helped me achieve better results and often made my work faster and easier.
An Interesting AI Coding Experience
Recently, I was working on a project that required writing code in a technology I hadn’t used for more than five years. Instead of refreshing my memory, I decided to ask one of the popular LLMs to generate this code for me. It created more than 400 lines of good, working code, and I was fully satisfied. I merged the code into the project and moved on.
Then, the next day, I had to implement a similar task. At first, I began coding it myself, out of habit. Then I realized - wait, why not use AI again? So I did, and once again, the results were great.
But then, on another day, I found myself writing code manually again - without thinking. Why? The AI-generated code had been good. It worked. So why didn’t I turn to AI first this time?
I began to reflect. The action felt unconscious, like my brain just defaulted to the old way of working. Was it habit? Resistance to change? Or something deeper?
A Scientific Research About Over Relying on AI
Curious about why I kept returning to manual work despite AI’s success, I began looking into research about how AI affects our thinking. That’s when I came across a fascinating study: Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. The research explored how using AI for writing tasks affects our memory and brain activity. It introduced the term “cognitive debt” - a side effect of letting AI do the hard thinking for us. Here’s what it means:
- Your brain skips a workout. When AI does the thinking, your brain doesn’t engage or strengthen the skills needed for memory and reasoning.
- Learning doesn’t stick. People who used AI couldn’t recall what they “wrote” because their brain didn’t actively process the material.
- Long-term skill decline. Relying on AI too much may weaken problem-solving abilities over time.
My Personal Realization
This is exactly what happened to me. I’ve always kept my brain active, learning constantly. But suddenly, AI was doing all the work. Naturally, my brain resisted - trying to stay in shape by forcing me to think instead of relying on automation.
Out of curiosity, I re-checked the AI-generated code. It still worked fine, but on closer review, I spotted inefficiencies and logic I would’ve handled differently. Why didn’t I see them earlier? Most likely, because I was mentally “checked out.” The job seemed “done,” so I didn’t dig deeper.
When AI writes an email for me, I review it carefully. But when it generates 400 lines of working code, it’s harder to stay vigilant - especially when the output already looks good.
What Should We Do?
Should we stop using AI? No. The genie is out of the bottle. But we should treat AI like a junior team member - useful, knowledgeable, fast, but still learning. Just like we guide junior developers, we must review and improve what AI creates.
We need to stay critical, think actively, and not outsource our brain. If we blindly accept AI outputs, we risk losing the very skills that made us effective in the first place.
Conclusion: Stay Human
AI is a powerful tool - but not a replacement for thinking. Don’t stop using your brain. Don’t stop reviewing, questioning, learning. Let AI help, but don’t let it make you passive.
Don’t stop thinking. Train your brain. Be human.