Introduction
As a mechanic, my days were spent diagnosing and repairing complex engines—a skill I took great pride in. Over time, however, I discovered a new hobby I had never considered before: coding. What started as a casual interest quickly turned into a passion that opened my eyes to endless learning possibilities and unlimited growth. At 31, I decided it was time to turn that passion into a career.
I had no prior experience with coding, but the idea of building something from scratch, solving intricate problems, and exploring a field full of opportunities was thrilling. Initially, I wasn’t sure where to start, but a friend introduced me to ChatGPT. They were learning React—a programming framework I didn’t understand at the time—and showed me how they used ChatGPT to navigate challenges.
That introduction marked the beginning of an exciting transition. ChatGPT became my virtual mentor, guiding me step by step as I shifted from repairing engines to writing code. While I truly enjoyed my work as a mechanic, coding offered a sense of unfamiliarity and excitement that kept me coming back for more.
The Transition: From Tools to Tech
My experience as a mechanic taught me valuable skills: patience, attention to detail, and methodical problem-solving. To my surprise, these skills aligned seamlessly with coding. Whether diagnosing an engine or debugging a program, both require breaking down problems into manageable parts and finding effective solutions. This unexpected overlap made the transition feel natural and reaffirmed my decision to pursue this new path.
The difference? While mechanical work is finite, coding is boundless. I could build apps, automate tasks, or dive into artificial intelligence. This potential ignited my curiosity, and I was ready to learn—but I needed guidance.
How ChatGPT Became My Guide
When I started, I didn’t even know how to ask the right questions about coding. But through trial, error, and a bit of persistence, I crafted prompts that made ChatGPT an incredible teacher. Here are a few that transformed my learning process:
Building Syntax Knowledge One Line at a Time
Prompt:
“You are an AI teacher tasked with guiding me through the syntax of a programming language. Provide code one line at a time, explain it thoroughly, and ask if I understand before moving forward.”Impact:
This method felt approachable, especially as a beginner. By learning one line at a time, I could focus on the purpose and syntax of each part before moving on — mirroring the step-by-step process I used in engine diagnostics.
Mastering Data Structures with Context
Prompt:
“Explain why we’re using certain data structures, like dictionaries or lists, and suggest alternative ways to achieve the same result. Break down their purpose in detail.”Impact:
This prompt was a game-changer. Understanding data structures felt overwhelming at first, but these explanations made them relatable. Choosing the right data structure started to feel like selecting the perfect tool for a repair job.
Labs with Gradual Complexity
Prompt:
“Create 7 labs, starting simple and gradually increasing in difficulty. Walk me through each solution step-by-step, asking if I understand before moving forward.”Impact:
This structured approach gave me confidence. Each lab built on the last, creating a clear learning progression. It reminded me of moving from basic repairs to more advanced diagnostic challenges in the workshop.
- Encouraging Hands-On Learning
Prompt:
“Guide me through typing each line of code, specifying where to place it. Correct my mistakes and explain why the code is written this way. Always check if I understand before moving forward.”Impact:
Typing each line myself, with ChatGPT’s guidance, reinforced my understanding and helped me debug issues independently.
Why This Method Worked
Personalized Learning: These prompts catered to my pace and knowledge level.
Encouraging Feedback: ChatGPT provided positive reinforcement while gently correcting mistakes.
Concept Reinforcement: Repetition and gradual progression made abstract ideas concrete.
Example:
The image below shows a lab exercise from my Introduction to Programming with Python course at Western Governors University. After reading the chapter on file handling, I found myself struggling to complete this lab independently. I wanted to gain the confidence to solve similar problems on my own in the future. To build my skills, I decided to practice on progressively challenging labs.
I provided the following prompt to my AI for assistance:
"The lab below is too advanced for me to solve alone. Please create 7 labs that gradually increase in difficulty, starting with the simplest version of the lab and ending with the final lab shown here. For each lab, guide me step-by-step, allowing me to type each line as I learn. Correct my mistakes as we progress and explain why we are using specific data structures like dictionaries, lists, or functions. Offer alternative approaches and describe the structure and purpose of these elements in detail. Ensure I understand each step before moving forward. Include comments for every line of code, explaining its purpose.".
By the time I reached Lab #6, I had developed a clear understanding of the concepts and was able to complete Lab #7 independently without any further assistance from AI. This method not only helped me grasp the necessary skills but also reinforced my learning for long-term retention.
Conclusion: A Journey Fueled by Curiosity
When I started learning to code, I didn’t even know ChatGPT existed. Now, with its help, I’ve gone from someone who didn’t understand programming languages to someone who enjoys solving coding challenges.
Switching careers at 31 was intimidating, but this leap has been the most rewarding decision of my life. If you’re a mechanic—or anyone in a hands-on profession—considering coding, know this: the skills you’ve built in your current job are more transferable than you think.
With the right tools, mindset, and guidance, your growth opportunities are truly unlimited.