Coding with AI
15 Dec 2025
Introduction
In the field of software engineering, artificial intelligence has changed the way software is designed, developed, and maintained. AI tools can help improve productivity by assisting with coding, finding bugs, and speeding up development. In my ICS 314 class, I used AI as a tool to help me better understand concepts and complete assignments more efficiently. However, as we use AI, it is important that we still put in the effort ourselves so that AI is not just thinking for us.
Experience WODs
I found it unnecessary to use AI for the experience WODs. I relied more on the solution videos, which guided me step-by-step, and I would simply redo the WOD until I finished it in a faster time frame.
In-class Practice WODs
I tried to complete the practice WODs on my own, but as the class became more difficult, I started using AI tools like ChatGPT to generate the basic layout of the code, which helped a lot. I also asked ChatGPT to create similar versions of the practice WODs and timed myself while solving them.
In-class WODs
I did use AI to help me with in-person WODs. I would code as much as I could on my own, and when I got stuck, I would have ChatGPT help me write the rest of the code. I also used the practice WODs and experience WODs as examples to give ChatGPT a layout or format to build off of, and then I adjusted the generated code to match our assignment so it would run correctly.
Essay
I have it fix my grammar errors and make my writing more clear.
Final project
The issues I worked on were heavily assisted by AI, specifically the VS Code Copilot. I found it extremely helpful in guiding me toward the correct approach and clarifying what needed to be done. The issues were quite complex and time-consuming, so much of my code was developed with Copilot’s assistance, especially in structuring solutions and troubleshooting problems. While most of my code was generated by AI, I made sure to understand how it works because I didn’t want to be clueless about what it meant or why it worked.
Learning concepts/ tutorials
I used AI tools such as ChatGPT to expand on topics I was not very familiar with. It helped break down lessons into smaller, simpler parts, making the material easier to understand and apply.
Answering a question in class or in Discord
The professor incourage to ask chatgpt to answer the questions in class so i did. But i didnt use AI for any of the discord questions mainly because i didnt answer any of them.
Asking or answering a smart-question
I didn’t ask a lot of questions or answered any of the smart-questions so i didnt use AI for any of them.
Coding example
I used AI to break down code that I didn’t understand and then asked it to provide additional examples of how that code could be used in different ways.
Explaining code
I found AI really helpful when it came to explaining code. By asking it to break the code down into simpler terms, it made the material much easier to understand.
Writing code
As we progressed in class, I began heavily relying on AI to generate my code, especially for the final project. For example, when building my Prisma schema, I wrote a detailed description of what I wanted it to do and had Copilot generate the code for me. I set strict guidelines to ensure the generated code followed my instructions, and I often read through the code carefully to understand exactly what it was doing.
Documenting code
I wrote a basic outline explaining what each part of the code meant, then used Copilot to write instructions on what the code was doing.
Quality assurance
I relied on Copilot to help fix errors since it was easier than manually searching through large amounts of code. However, there were times when Copilot claimed an issue was fixed but the problem remained, so I had to go in and fix the code myself.
III. Impact on Learning and Understanding:
AI changed the way I learned coding in both good and bad ways. It helped me understand concepts faster and gave clear examples, but I ended up writing less code myself. While AI improved my understanding, it also reminded me that real skill comes from practicing on my own.
IV. Practical Applications:
AI does a good job at generating basic code, so I can see it being used in that way. However, it still needs people to review the work to make sure it’s correct.
V. Challenges and Opportunities:
AI is very helpful, but it has faults. When generating code, you need to give clear instructions and strict guidelines, or it can create errors or mess with existing code. Despite this, AI can guide learning, give examples, and provide practice problems. In the future, it could be used more in education for tutoring, code reviews, and interactive exercises while still encouraging hands-on coding.
VI. Comparative Analysis:
AI can be very useful for online lessons and textbook reading, making learning more efficient and providing personalized examples for students. For coding, AI is best used as a tool to review and understand code, rather than writing it for you. Traditional teaching helps build hands-on skills, while AI can enhance understanding and engagement, but both are important for fully learning software engineering.
VII. Future Considerations:
AI will likely play a bigger role in software engineering education. It could help students learn faster with personalized lessons and feedback. The challenge is making sure students don’t rely on it too much and still practice coding themselves.
VIII. Conclusion:
AI has been both helpful and challenging in this course. It made learning concepts faster, provided examples, and guided me through difficult coding tasks, especially for the final project. However, relying on AI too much limited my hands-on coding practice and sometimes required careful review to avoid errors. Overall, AI is a powerful tool for learning and understanding, but students still need to practice coding themselves. For future courses, AI could be integrated as a supportive resource—helping with explanations, examples, and feedback—while encouraging independent problem-solving to build real skills.