Recently, I happened to have a few conversations with parents and people close to me whose kids or friends are graduating in the next 6 months. One question kept coming up: “With AI changing so much, what should a student actually learn now?”
Questions like:
“With AI changing so much, what should a student actually learn now?”
“Is learning coding still useful?”
“AI is doing everything a junior developer used to do. Then how will freshers get experience?”
“Do they need to become AI Engineers now?”
“Won't companies prefer experienced people who can use AI?”
Honestly, these are very valid questions.
I had the same thought when I started thinking about how different things are today compared to when I started as a junior developer.
When I joined as a junior Python developer, I spent my early days doing things like writing test cases, running database queries, fixing small bugs, writing automation scripts and understanding an existing codebase.
Those were simple tasks, but they taught me how software actually works.
Today, AI can do a lot of those things.
So yes, things have changed.
But please don't panic. 😄
First: Coding is NOT dead
You still need to know programming.
But don't learn Python/Java/JavaScript just to write code line by line.
Learn enough to understand code, debug it, change it, and build things with it.
AI can write code for you now. That's actually good!
Your job is to know:
What should I build? Does this code make sense? Does it work? What happens when it breaks?
That's becoming more important.
Myth: "I have to become an AI Engineer"
Nope.
This is probably the biggest confusion I see.
Companies still need software engineers.
Backend developers, frontend developers, full-stack developers, automation engineers, data engineers, QA engineers, and many others.
The difference is becoming:
Software Engineer + AI tools
rather than:
Software Engineer without AI.
You don't need to start with RAG, multi-agent systems, LangGraph, MCP, fine-tuning, etc.
Those are things you can learn later when you actually need them.
Don't turn every trending AI technology into your college syllabus. 😄
So what should you learn?
Keep it simple.
Pick ONE programming language.
Python / Java / JavaScript / Go — any one is fine.
Then learn:
- SQL
- Git & GitHub
- APIs
- Databases
- Basic testing
- Debugging
- Basic deployment
Then learn how to use AI tools effectively.
That's enough to start.
You don't need to know everything.
You need to know something well enough to build with it.
"But building projects is expensive!"
Not really. 😄
This is another thing I hear a lot.
You can build surprisingly good projects with free or cheap tools.
AI: OpenRouter, NVIDIA offerings, Gemini free tiers, or local models with Ollama.
Hosting: Vercel and other free-tier platforms.
Database: Supabase / Neon.
Code: GitHub.
You don't need an expensive AWS account or a $500/month AI setup.
And you don't even need to buy a domain.
Build it. Put it on GitHub. Record a demo. Share it.
That's already proof of work.
What should your projects look like?
Please don't build another:
Calculator 😭
Todo app 😭
Weather app 😭
Build something that solves a real problem.
For example:
College Placement Tracker
Then add:
AI Resume + Job Matching
Now you've demonstrated:
Programming + Database + APIs + AI + Deployment.
One good project can teach you more than 10 tutorial projects.
And don't worry if the first version is simple.
Build → break → fix → improve.
That's how you actually learn.
And how do you get the job?
Don't only do:
Apply → Wait → Reject → Repeat
Find startups, small companies, founders, engineering teams, internships, open-source projects, etc.
And show them what you built.
Instead of:
"Hi sir, I'm a fresher looking for a job."
You can say:
"I built this project, here's the demo and GitHub. I'm graduating soon and looking for an entry-level opportunity."
Show, don't just tell.
Your first job doesn't have to be your dream company.
Your first goal is to get real experience.
One last thing ❤️
Don't panic when you see someone on LinkedIn saying:
"You MUST learn Agents + RAG + MCP + LangGraph + 27 other things."
You don't.
Your goal isn't to become an AI expert before graduation.
Your goal is to become a good software engineer who knows how to use AI to work faster.
Learn the basics.
Build things.
Break things.
Fix them.
Ask AI questions.
Use AI to learn.
And slowly become better.
You have 6 months.
Don't try to learn everything.
Just get 1% better every day. ❤️
You might be surprised where you end up by graduation.
And to all the parents, brothers, sisters, friends and soon-to-be graduates asking these questions:
Yes, the market is uncertain.
Yes, AI is changing entry-level work.
But that doesn't mean you should give up or try to learn everything at once.
The goal isn't to beat AI.
Learn to build with it.
A small note from me ❤️
If you're a student, parent, or someone in the same situation and have doubts, don't hesitate to reach out or ask.
I'm still learning too.
Let's figure things out, share what we learn, and grow together.
Still learning. Still building. Still curious. — Ram Bikkina
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