I have a computer science degree with a specialization in AI and Data Science. And I still didn't know what prompt engineering actually was.
Not really. Not until three weeks ago.
That's the honest starting point.
I graduated, looked at my skills, and realized that a lot of what the real world is talking about — GenAI, prompt design, modern full-stack tools — either wasn't covered in my coursework or just went past me without landing.
I could have waited until I felt ready. Instead, I decided to relearn it in public.
Who I am
Fresh engineering grad. Coimbatore-based. Interested in AI and full-stack development, and currently figuring out how to get better at both at the same time.
I'm not here to perform expertise I don't have. I'm here to build, document what I learn, and eventually land a job that lets me keep doing this.
What I'm relearning and building
Four things on my plate right now:
- AI/ML fundamentals — from the ground up, not just theory
- MERN stack — building real full-stack projects
- React → Next.js — making the transition properly
- JavaScript → TypeScript — because I keep seeing it everywhere and I need to stop avoiding it
These aren't goals I set to sound ambitious. They're the gaps I noticed when I looked at job listings and got honest with myself.
Where I am right now
Started with Elements of AI from University of Helsinki — low pressure, good foundation reset.
Then Generative AI for Beginners from Google.
Currently working through the IBM Applied AI Developer Professional Certificate. Three courses done:
- Introduction to AI ✅
- Generative AI – Introduction and Applications ✅
- Generative AI – Prompt Engineering Basics ✅
Three more to go.
The prompt engineering course is where something actually clicked. I'd been using ChatGPT and Claude for a while and thought prompts were just — type what you need, maybe fix your grammar, get an answer.
Turns out prompts have types. Paradigms. Building blocks. There are tools built specifically to optimize them. I had seen "prompt engineering" mentioned a hundred times and never actually understood what it meant.
The fact that I specialized in AI in college and still missed this says a lot about the gap between academic curricula and where the field actually is.
What comes next
Projects. Real ones.
I'll share what I build, what breaks, what I figure out, and what I wish someone had told me earlier — not just polished final results, but the messy middle too.
I'll also share dev news and tools I come across that seem worth passing on. This won't only be about my own work.
The honest goal
I want to land a job in AI or full-stack development. Not hiding that.
But I also want to keep growing after I get there. Building in public is how I plan to stay accountable — not just during the job hunt, but after it.
If you're in a similar phase — relearning, rebuilding, or just starting out — I'd genuinely like to hear from you.
What's one thing you wish your college had actually taught you about working in tech?
Drop it in the comments. Let's compare notes. 👇
Top comments (9)
too close to home 🏃🏻➡️.
just don't wait to know everything before you start making projects. it got a little better for me when i accepted every project doesn't need to be a 100% polished "resume project", treat them like your assignments to track how much you've learnt so far
I can relate to that. I experienced something similar in my first year. Now, I’m focusing on the fundamentals again so that I can properly execute my project ideas. However, I know that the real learning will happen while I’m building my projects.
Really relate to this 👍
That gap between what we learn in college and what the industry actually expects is very real, especially in AI and modern web dev. I like the approach of “relearning in public” it keeps things honest and also makes the journey more structured.
Also agree on prompt engineering it looks simple at first, but once you go deeper, there’s a lot of structure and technique behind it. Looking forward to seeing what you build next
Thank you for your support buddy!!!
I will give my best!!!
That line about specializing in AI and still missing what prompt engineering actually was—that's not a failure on your part. It's a timestamp on how fast the ground shifted under everyone. The curriculum that was designed four years ago was built for a world where "AI" meant something different than it does today. You didn't miss it. It moved into the frame after the syllabus was already printed.
What I think you're actually doing, whether you meant to or not, is building a parallel education next to the one you already paid for. And that's not a weakness—it's becoming the norm. The degree gives you the theoretical scaffolding. The self-directed learning fills in the operational gaps. The fact that you can articulate which specific courses you're taking and what clicked in each one suggests you're already better at self-assessment than a lot of people with twice your experience.
The prompt engineering course being the thing that clicked is interesting, because that's a field that barely existed when you started your degree. It's also a field that might not exist in its current form by the time you're mid-career. The meta-skill you're practicing isn't prompt engineering—it's the ability to notice a gap, find resources, and close it without waiting for someone to structure it for you. That's the thing your college probably couldn't teach you, because it's not a subject. It's a reflex. Curious which of the three remaining IBM courses you're most looking forward to, and which one you're dreading—usually there's one of each.
The “timestamp” framing actually makes a lot of sense; I hadn’t thought of it that way before. The point about parallel education really resonates with me at this moment. You’re spot on about the meta-skill — I’m trying to improve my ability to notice gaps and fill them, rather than just focusing on the tools themselves. I’m looking forward to the upcoming hands-on, project-focused course, though I’m probably dreading the more theory-heavy one — but that’s typically where the real learning occurs.
the gap between degree and real-world is something nobody warns you about. starting over in public is uncomfortable - that discomfort is usually the sign you picked the right thing.
thank you so much for your kind encouragement
it does. keep building - the discomfort is proof you're on the right track.