For a long time, I believed coding was only for people who studied computer science or worked as professional developers.
Whenever I saw a screen filled with code, it looked like a completely different language. There were brackets, symbols, functions, and terms I did not understand. I assumed learning it would require years of study before I could create anything useful.
That changed when I encountered a repetitive task at work.
I was regularly copying information from a spreadsheet, checking each row, preparing an email, sending it, and updating the status manually. The work was manageable, but completing the same process repeatedly took time and left room for mistakes.
I started wondering if the spreadsheet could do some of the work for me.
That question led me to Google Apps Script.
At first, I did not even know where to begin. I understood the result I wanted, but I did not know how to translate it into code. I could explain the process clearly to another person, but explaining it to a computer felt different.
AI became my starting point.
I described the task and asked it to create a script. Within seconds, it gave me several lines of code. I copied them, ran the script, and immediately received an error.
My first reaction was frustration. I had expected the code to work because it looked complete. But I soon realized that generated code was not automatically working code.
I went back and explained the error. AI suggested a change, so I tested it again. Another issue appeared. I repeated the process until the automation finally worked.
The moment it worked, something changed in the way I viewed coding.
I did not suddenly become a programmer, but I had created something useful. A task that previously required several manual steps could now happen automatically.
I became curious about what else I could build.
I started experimenting with confirmation emails, timestamps, form submissions, missing-data checks, and automatic reports. Each project introduced me to a new concept. I learned about variables because I needed to store information. I learned about conditions because the script needed to make decisions. I learned about triggers because the automation needed to know when to run.
Instead of learning these concepts only through definitions, I learned them while solving actual problems.
There were still many mistakes. Sometimes I used the wrong column number. Sometimes a script worked during testing but failed when another person used the spreadsheet differently. Sometimes I spent hours fixing a problem caused by one missing character.
Those experiences taught me to read error messages, test different situations, and ask more specific questions.
They also taught me not to rely completely on AI.
AI can provide a starting point, explain unfamiliar code, and suggest possible fixes. However, I still need to understand what the script is doing. If I copy code without understanding it, I will not know what to do when the workflow changes or something stops working.
I am still learning, and there is a lot I do not know. But I no longer see coding as something reserved only for professional developers.
Coding can also be a practical tool for people who want to solve everyday problems, improve workflows, and save time.
Sometimes, learning does not begin with memorizing a programming language. It begins with noticing a problem and becoming curious enough to ask:
Is there a better way to do this?