DEV Community: Anushka Shinde

Impostor Syndrome in Tech - The Honest Version Nobody Posts About

Anushka Shinde — Thu, 28 May 2026 16:57:21 +0000

Let Me Tell You Something Embarrassing

I got selected for a placement opportunity at my college.

Out of everyone including people who code better than me, people with better grades,people who I genuinely thought deserved it more

I got selected.

And my first thought wasn't excitement.

It was "why me?"

What Impostor Syndrome Actually Feels Like

Not the LinkedIn version where someone says"I still feel like I'm learning every day!"

The real version.

The version where you see someone's resume and feel your stomach drop.Where you pass an interview and think "they made a mistake."Where you build a project and feel guilty because AI helped you write the code. Where you have certifications but know that lakhs of other students have the same ones.Where nothing feels unique enough.Where nothing feels like enough.

That version.

The Placement That Confused Me

A company came to my college.
They wanted resumes.They shortlisted fifteen to twenty people.

Some of the best coders in my batch didn't get shortlisted.
Maybe their resume structure wasn't right.Maybe it was luck.
Maybe the system is just that unpredictable.

But I got selected.

And then I got the internship opportunity.

When I went the experienced people there were genuinely impressed.Not by my grades. Not by my CGPA.By my curiosity.

The fact that I touched different technologies not because my syllabus demanded it but because I wanted to know what they felt like.

That meant something to them.

And in that moment I realized a lot of people don't know what I know.Just like I don't know what a lot of people know.

Nobody is complete.
Not even the seniors.

The AI Guilt Nobody Admits

Here's something I've never seen
anyone write about honestly.

Most of my projects I choose the idea.I design the system. But the development phase?AI writes a significant portion of the code.

And I feel guilty about it every single time.

Like I didn't really build it.
Like if someone looked closely enough they'd see the seams.
Like I'm presenting something as mine that isn't fully mine.

But here's what I've slowly started understanding —

I chose what to build.I understood the problem.I designed the solution.I knew when something was wrong.I explained it to experienced people
and they were impressed.

The tool doesn't define the builder.A carpenter who uses a power drill didn't build less than one who used a hand saw.

The guilt is real.But so is the work.

The Certification Trap

I look at my certifications and think thousands of people have these exact same ones.

IBM. AWS. HackerRank.Every student is collecting them.
Every resume looks the same.

What makes mine different?

And then I remember certifications are not the proof.
What you do with the knowledge is.

The person who completed AWS certification and then wrote a blog post explaining cloud cost optimization to other students that person stands out.

Not because of the certificate.
Because of what they did after.

The JavaScript Confession

I don't like JavaScript.

I said it.

It doesn't feel logical to me.
The syntax feels inconsistent.
PHP feels similar rules that don't always make sense.

In one interview they asked me JavaScript questions.I told them honestly "I learned it in bachelor's but I'm not
comfortable with it right now."

They said "That's fine. We work with JavaScript a lot here.It's actually the language behind React, TypeScript, Angular."

And I felt small for a second.
Because I use React.And I don't like the language it's built on.

But they weren't bothered.
They valued the honesty more than the knowledge.

The Jealousy That Actually Helps

Someone in my batch built something I wish I had built.

I won't call it pure jealousy.
It was jealousy mixed with curiosity mixed with a fire that said I want to build something better than that.

And that feeling uncomfortable as it is is the most productive feeling I've ever had as a developer.

When someone is better than me I don't want to bring them down.I want to reach their level.And then go further.

That jealousy became projects.
Those projects became my portfolio.That portfolio got me selected.

What I Know Now

Someone will always be better than you.Always. In every room. At every level.

Even when I join a company I'll look at seniors and think "they know so much more than me."

And that will light a fire.And I'll learn everything they know. And then I'll want to know more.

That's not impostor syndrome winning.That's impostor syndrome becoming fuel.

The difference between developers
who grow and developers who freeze is what they do with that feeling.

Freeze and you stay stuck.Move anyway and the feeling slowly starts to feel less like fear
and more like direction.

Final Thought

You are not a fraud.

You are someone who hasn't learned everything yet.
Nobody has.
Nobody ever will.

The impostor feeling means you care.It means you have standards.
It means you know there's more to learn.

That's not a weakness.
That's exactly the kind of person
a good company wants to hire. 😊

When did you last feel like an impostor?
And what did you do with that feeling?

Drop it honestly below 👇
Not the polished version.
The real one.

Why Every Developer Needs a Digital Presence in 2026 - Even If It Feels Like Showing Off

Anushka Shinde — Tue, 26 May 2026 09:45:32 +0000

I Used to Find LinkedIn Annoying

When I first joined LinkedIn in 2024 I was frustrated.

Everyone was posting about:What they learned.What they achieved.
What certifications they got.
What companies they interviewed at.

It felt like showing off.It felt performative.It felt like nobody was being real.

And then I realized something
that changed how I see everything.

Companies Are Watching

When a company looks for an employee they don't just look at your resume.

They look at your LinkedIn.
Your GitHub.Your blog.Your online presence.

And what they're looking for is not just your skills they're looking for a social animal.

Someone who communicates.
Someone who shares knowledge.
Someone who shows up consistently.Someone who is active, engaged, and present in their field.

Because here's the truth when that employee represents the companyin front of a foreign team,a foreign client,an international stakeholder

They need someone with:
Good communication.Good values.
Good understanding of their field.And proof that they can present themselves well.

Your digital presence is that proof.

The Shift That Changed Everything for Me

Once I understood WHY people post the frustration disappeared.

They're not showing off.They're building evidence.

Evidence that they know things.
Evidence that they're growing.
Evidence that they're worth hiring,worth collaborating with,
worth trusting with real work.

And when I started building my own GitHub with real projects,
DEV.to with honest blogs,
LinkedIn with actual achievements
I stopped feeling invisible.

What Digital Presence Actually Means

It doesn't mean posting every day.It doesn't mean fake achievements.It doesn't mean pretending to be someone you're not.

It means showing what's real.

GitHub shows you actually build things.Not just talk about building them.

DEV.to or any blog shows you can explain what you know. Explaining something well proves
you understand it deeply.

LinkedIn shows your professional journey.Where you've been. What you've learned.Who you've worked with.

Together they tell a story
no resume ever could.

The Developer Who Gets Hired

Two freshers. Same skills. Same college.Same tech stack. Same CGPA.

One has:

GitHub with 3 real projects
10 blog posts about what they built
Active LinkedIn with certifications posted
A digital trail that proves their journey

One has:

A resume
Nothing else

Who gets the callback?

You already know the answer.

The Uncomfortable Truth About Staying Silent

Staying quiet about your achievements doesn't make you humble.

It makes you invisible.

In a world where hundreds of freshers are applying for the same role the ones who are visible online have already won half the battle before the interview even starts.

Your skills are real.Your projects are real.Your journey is real.

But if nobody can see them they might as well not exist.

What to Start With — Today

You don't need to do everything at once.

Start with one thing:

If you have projects push them to GitHub.If you have certifications add them to LinkedIn.If you have experiences write one honest blog post.

That's it.One thing.Build from there.

The goal is not to become a LinkedIn influencer.The goal is to make sure that when a recruiter searches for someone like you they find you.

And when they find you they see someone real,someone consistent,
someone worth reaching out to.

Final Thought

I used to think digital presence was for people who loved attention.

Now I understand it's for people who want opportunities.

In 2026 your skills get you in the room.Your digital presence gets you the invite.

Start building yours. Even if it feels uncomfortable.Even if it feels like showing off.

Because somewhere right now a recruiter is searching for someone with exactly your skills.

Make sure they can find you. 😊

When did you realize digital presence matters?
Or are you still on the fence about it?

Drop your honest take below 👇

Open Source AI vs Closed AI - A Fresher's Honest Take on Which Side to Be On

Anushka Shinde — Mon, 25 May 2026 13:30:09 +0000

Everyone Is Picking a Side

Open Source AI or Closed AI?

Developers are debating this everywhere.LinkedIn. Twitter. Tech conferences.

So let me give you the most honest answer I can not from an expert.From a fresher who uses AI every single day and is just now understanding what this debate actually means.

What I Actually Use And Why

I use Claude. ChatGPT. Gemini.

All closed AI. All daily.

Not for anything complicated.
Not for anything confidential.
Not for anything that carries
serious responsibility.

I use it to understand concepts
my teachers explain poorly.To prepare for exams.To build projects.To write blogs like this one.

For a student closed AI is everything.It's accessible. It's free tier friendly.It just works.

And honestly?
That's enough for where I am right now.

What Open Source AI Actually Is

On the other side Meta's Llama. Mistral. DeepSeek.

The code is publicly available.
You can download it.Run it on your own computer.Modify it. Customize it.Your data never leaves your machine.

Companies build their own AI products using these models as a foundation.

Sounds powerful. Because it is.

The Privacy Conversation Nobody Is Having

Here's something that made me think seriously.

India's Finance Minister recently warned RBI chiefs and bank heads be careful about which AI agents
you allow into your systems.

Because some of the most powerful
AI agents being used today used by only a handful of companies like Microsoft and Google come with serious data implications.

When confidential banking data,
government data ,or company trade secrets touch a closed AI system where does that data go?

Who stores it?
Who trains on it?
Who owns it?

These are not paranoid questions.
These are questions that regulators are now asking officially.

And THIS is where open source AI
suddenly makes complete sense.

When Each Side Actually Makes Sense

Closed AI — for students and individuals

Learning and understanding concepts
Building personal projects
Exam preparation
Writing and content creation
Anything where privacy isn't critical

Free tier. Accessible. Powerful enough.Perfect for where most of us are right now.

Open Source AI — for companies and professionals

Handling confidential client data
Building internal company tools
Healthcare and banking applications
Government systems
Anything where data cannot leave your own infrastructure

When responsibility increases the need for control increases.Open source gives you that control.

My Honest Prediction as a Fresher

Right now I don't fully understand the importance of open source AI.

I know it exists.I know it's powerful.I know companies use it.

But I haven't needed it yet.

The day I join a company the day I handle real client data,real confidential systems,real responsibility

That's when open source AI will matter to me.

And I want to be ready for that day before it arrives.

What This Means for Developers

If you're a student like me closed AI is fine. Use it. Learn from it.It's not cheating. It's a tool.

If you're entering a company start understanding open source options.Llama. Mistral. DeepSeek.
Know they exist and why companies choose them.

If you're handling sensitive data closed AI is not the answer.
Open source running on your own
infrastructure is.

The side you should be on depends entirely on what you're building and who it affects.

Final Thought

This debate isn't really about
which AI is better.

It's about responsibility.

As a student my responsibility is low.Closed AI serves me perfectly.

As a professional responsibility grows.And with it the need for control,transparency, and data ownership grows too.

Pick the tool that matches
your level of responsibility.
Not the one that's most popular. 😊

Which side are you on right now?
And has your opinion changed
as your responsibility in tech has grown?

Drop your honest take below 👇
Especially if you've worked with
open source AI in a real company I genuinely want to know how it felt compared to closed AI tools.

Are Junior Developer Roles Actually Dying? A Fresher's Honest Take

Anushka Shinde — Mon, 25 May 2026 13:20:35 +0000

Everyone Is Asking This Question

Are junior developer roles disappearing?

I've seen it debated on LinkedIn.
I've felt it while applying for jobs.I've thought about it as someone who is literally entering this industry right now.

So let me give you the most honest answer I can not from a senior developer's perspective.

From a fresher who is living this reality.

The Comparison Nobody Wants to Make

Let's be honest about what's actually happening.

A senior developer has two options today:

Option 1 — Hire a junior developer
Explain the task.
Junior develops it.
Runs test cases.
Fixes bugs.
Reports back.
Costs a full salary every month.
Comes with human error risk.
Comes with onboarding time.

Option 2 — Use an AI agent
Explain the task via prompt.
Agent develops it.
Runs test cases automatically.
Fixes bugs.
Reports back.
Costs a subscription.
Faster. Available 24/7. No sick days.

When you put it this way the math is uncomfortable.

But Here's What AI Can't Replace

Privacy.

This is something nobody talks about enough.

When you give your codebase to an AI tool you are sending company confidential data to a cloud system.

Some of that data is stored.
Some of it trains future models.
Some companies have already banned AI tools internally because of this.

A junior developer signs a contract.An NDA. A confidentiality agreement.
Legal consequences if they leak data.

An AI agent has no such accountability.

And ironically a junior developer using AI for their work creates a double privacy risk.Human + AI both touching confidential data.

There is no perfect solution here.Just different risks.

What I Actually See in Job Listings

When I apply for jobs I see mostly senior roles.3 to 5 years experience required.

Junior roles exist but they're fewer.And here's why I think that is:

People don't stay junior for long.

Join a company for 2 years you're already a mid level developer.
3 years you're senior in many companies.

The "junior developer" label disappears fast not because the role disappeared but because people move through it quickly.

The Fear Is Real. But So Is the Opportunity.

Yes. I feel threatened sometimes.

As someone completely dependent on AI for my studies, my projects, my learning I know exactly how capable these tools are.

If I can use AI to build a full stack project so can an AI agent.
Faster. With fewer errors.

But here's what I keep coming back to:

Even if I build something with AI I added something the AI couldn't.

My understanding of the real problem.My conversation with the actual user.My judgment about what matters and what doesn't.
My ability to say "this doesn't feel right"even when the code technically works.

AI generates. Humans decide.
That gap however small it gets
is where junior developers still live.

My Honest Prediction

Junior roles won't disappear completely.But they will change.

The junior developers who survive will be:

The ones who use AI as a tool not a crutch
The ones who understand what they're building not just how to prompt it
The ones who bring human judgment to AI generated work
The ones who communicate, collaborate , and think things agents still struggle with

The junior developers who disappear will be:

The ones who only know how to copy paste
The ones who can't explain their own code
The ones who stopped learning because AI was doing it for them

What I'm Doing About It

I'm a fresher entering this market right now.

I use AI every single day.
For projects. For learning. For writing this post.

But I make sure I understand what I'm building.I make sure I can explain every decision.I make sure I'm adding something real
not just prompting and submitting.

Because the day I can't explain my own work is the day an AI agent genuinely replaces me.

That day hasn't come yet.
And I'm making sure it doesn't. 😊

Are you a fresher feeling this fear too?
Or are you a senior developer who has
already replaced junior work with AI?

Drop your honest take below 👇
This conversation needs real voices not just LinkedIn optimism.

The Job Role Nobody Is Talking About and Why Freshers Should Get There First

Anushka Shinde — Sun, 24 May 2026 08:40:35 +0000

I Found Something Interesting

Everyone is rushing toward-
Full Stack Developer.
Data Scientist.
AI Engineer.

These are good paths.But they're also crowded paths.

Thousands of freshers. Same skills. Same certifications. Same projects.All applying for the same roles.

So I started thinking differently.

What does every company need right nowthat almost nobody is specializing in?

The answer surprised me.

Every Company Is Moving to Cloud

This is not new information.AWS. Azure. Google Cloud.Every company tech and non-tech is migrating to cloud.

But here's what nobody tells you
about cloud migration

It gets expensive. Fast.

Very expensive.

The Problem Nobody Warned Companies About

Cloud sounds simple pay for what you use.

But in reality?

Developers spin up servers and forget them
Storage buckets fill up with unused data
Licenses get purchased and never used
Resources run 24/7 when they're only needed 8 hours a day
Teams duplicate infrastructure without knowing

One medium sized company can waste lakhs of rupees every month
on cloud resources nobody is using.

A 2024 report found that companies waste an average of 32% of their cloud spend.

32%.

That's not a small problem.That's a massive, expensive, growing problem.

Enters The Cloud Cost Optimizer

This is not a widely recognized job title yet.That's exactly why I'm writing about it.

A Cloud Cost Optimizer is someone who:

Audits a company's cloud infrastructure
Identifies wasted resources
Recommends and implements cost saving changes
Monitors spending continuously
Balances performance with cost efficiency

Some companies call it FinOps.
Some call it Cloud Financial Management.Some don't even have a name for it yet they just know they're overspending and don't know why.

Why This Is a Fresher Opportunity

Here's the loophole

Senior developers don't want to do this.They want to build things.Create features. Solve engineering problems.

DevOps engineers are focused on
deployment and infrastructure.
Not cost optimization specifically.

Cloud architects design systems.
They don't audit spending daily.

Nobody owns this problem completely.And companies are feeling the pain of that.

A fresher who understands:

Cloud services and how they're priced
How to read AWS Cost Explorer or Azure Cost Management
Basic infrastructure auditing
How to identify idle or oversized resources
How to write a cost optimization report

Is genuinely valuable to any company using cloud right now.

What Skills You Actually Need

Cloud Fundamentals
AWS, Azure or Google Cloud basics.Understanding what each service costs and why.AWS Cloud Practitioner level is enough
to start.

FinOps Fundamentals
FinOps Foundation has free learning materials at finops.org/resources to understand cloud financial management concepts.

For actual certificates AWS Skill Builder has free courses on Cloud Cost Optimization and Cloud Financial Management.Complete those and add them to your profile.

Very few freshers have this knowledge.
That alone makes you stand out.

Cost Management Tools

AWS Cost Explorer
AWS Trusted Advisor
Azure Cost Management
Google Cloud Billing Reports

All free to learn on free tier accounts.

Basic Data Analysis
Reading cost reports.Identifying patterns in spending.Presenting findings clearly.

Excel or basic Python is enough.

What You Can Build as a Project

Cloud Cost Audit Report
Create a free AWS account.Spin up a few services.Use AWS Cost Explorer to analyze spending.
Write a report identifying waste
and recommendations.

This is a real deliverable.
Something you can show in an interview.Something most freshers have never done.

FinOps Dashboard
Build a simple dashboard that visualizes cloud spending by service, by region, by time period.

Use AWS billing API + any frontend framework.Suddenly you have a project that combines
cloud knowledge + development skills +cost awareness.

Nobody else in your placement batch will have this.

How to Position Yourself

Don't say "I want to be a developer."

Say "I'm interested in cloud infrastructure with a focus on cost efficiency and FinOps."

In a room full of freshers saying
the same thing you will be the one they remember.

Because every CTO is currently worried about their cloud bill.
And you just walked in understanding that problem.

Why This Will Only Get Bigger

Cloud adoption is accelerating.
Cloud bills are growing.
Companies are realizing they need
dedicated people managing this.

FinOps as a discipline grew 47%
in job postings between 2022 and 2024.

And it's still early.The freshers who position themselves here now
before it becomes a crowded field
will have a significant advantage
in the next 2 to 3 years.

Final Thoughts

You don't need to compete in the most crowded lane.

You need to find the lane that's
opening up right now before everyone else sees it.

Cloud Cost Optimization is real.
The problem is real.The demand is growing.And almost no fresher is positioning themselves for it.

That gap is your opportunity. 😊

Are you learning cloud right now?
Have you ever thought about the
cost side of cloud infrastructure?

Drop your thoughts below 👇
I'd love to know if anyone else
has spotted this opportunity!

Pressure Isn't Killing You -Your Relationship With It Is

Anushka Shinde — Sat, 23 May 2026 17:35:17 +0000

Everyone Is Telling You to Manage Your Time

Pomodoro technique.
Study schedules.
To-do lists.
Color coded planners.

You've tried them.They worked for two days.Then life happened and the plan collapsed.

So let me tell you something different.Something nobody puts in a productivity blog.

Pressure Is Not Your Enemy

Read that again.

Pressure is not your enemy.

Your relationship with pressure is.

Every CS student right now is facing the same storm placements, practicals, theory exams,coding rounds, HR prep, resume updates all at the same time.

The ones who survive it aren't the ones who had better schedules.

They're the ones who stopped fighting the feeling of being overwhelmed and started moving anyway.

The Psychological Trick Nobody Talks About

Your brain has one job when it feels overwhelmed make you stop.

Freeze. Scroll. Sleep. Avoid.
Anything to escape the feeling.

And the more you resist that feeling the stronger it gets.

So here's the loophole

Don't fight the overwhelm.
Acknowledge it.Then do one tiny thing anyway.

Not five things. Not a full study session.One thing. The smallest possible thing.

Open the coding platform.
Write one line of your resume.
Read one page of one subject.

That's it.

Your brain registers movement.
Movement breaks the freeze.
The freeze was the only real enemy.

The Comparison That Will Change How You See This

Think about a developer with 5 years experience.

They wake up every day with:

Fear of losing their job
Pressure to learn new technologies
Deadlines that don't care about their mood
Backup job applications running quietly
And if married — a whole life on top of that

They didn't get used to pressure.
They got used to moving through it.

You are training for exactly that right now in this exam season chaos.

Every time you show up when you don't feel like it you are building the most important
skill of your entire career.

Not Java. Not Spring Boot. Not AWS.

The ability to function under pressure.

The Real Loophole

Everyone is looking for a hack.
A shortcut. A secret formula.

Here it is

The students who do well during placement seasonare not the ones who prepared the most.

They are the ones who panicked the least.

And they panicked the least because they trusted what they already knew.

You already know things.Real things. Built things. Learned things.

Your projects are real.Your internship was real.Your certifications are real.Your struggle to get here was real.

No exam, no interview, no placement round can take that away from you.

Walk in knowing that.Not performing confidence.Actually knowing I have done real work.
I deserve to be here.

What To Actually Do This Week

Not a schedule. A mindset shift.

Stop preparing for everything.
Start preparing for the next one thing.

What is happening first?
Practical? Prepare for that.
Coding round? Prepare for that.
Theory exam? Prepare for that.

One thing at a time.Fully present for that one thing.Then move to the next.

The chaos feels like ten things
demanding your attention simultaneously.

It's not.It's ten things happening one after another.
Treat it that way.

Stop measuring by what's left.
Start measuring by what's done.

Every small win counts.One problem solved. One topic revised.One resume line improved.

Your brain needs evidence that
you are moving forward.Give it that evidence deliberately.

Stop waiting to feel ready.
Ready is a feeling that arrives
after you start not before.

You will never feel ready for a placement interview.You will never feel ready for a hard exam.
Nobody does.

The people who succeed showed up anyway.

For The Developers Reading This

You already know this is true.

The pressure never fully disappears.But at some point you stopped waiting for it to go away
and started building a life inside it.

What was the moment that shifted for you?What do you wish someone had told you during placement season?

Drop it below. Genuinely.
Not career advice. Human advice. 👇

Final Thought

You are not behind.
You are not failing.
You are not less than anyone else
in that placement room.

You are a student carrying more
than students were ever meant to carry and somehow still showing up.

That already makes you someone
a company should want.

Now go do the next one thing. 😊

What's the one thing you're doing today to move forward however small?

Drop it below 👇
Let's hold each other accountable.

Expert Systems -The AI That Existed Before AI Was Cool

Anushka Shinde — Thu, 21 May 2026 14:40:33 +0000

I First Heard About This in Class

Expert systems came up twice in my curriculum.Once in Management Information Systems.Once in Artificial Intelligence.

Both times I thought "this sounds incredibly intelligent and incredibly complicated."

Turns out it's both.
But also something any curious developer can understand and even build.

Let me explain everything.

What Is an Expert System?

An expert system is a computer program that mimics the decision-making ability of a human expert in a specific domain.

Not a general AI that knows everything.A focused system that knows one thing extremely well.

Think of it like this instead of asking a doctor every time you have a symptom,you ask a system that has been trained with a doctor's knowledge.

It asks you questions.It reasons through your answers.It gives you a diagnosis or recommendation.

That's an expert system.

How Is It Different From Modern AI?

This is the question everyone asks.

Expert System	Modern AI (ML/DL)
Rule based	Pattern based
Knowledge entered manually by experts	Learns from data automatically
Explainable — you can see why it decided	Often a black box
Works with limited data	Needs massive datasets
Specific domain only	Can generalise across domains
Built in the 1970s-90s	Dominant today

Expert systems are not better or worse than modern AI.
They are different tools for different problems.

Where explainability matters medical diagnosis, legal decisions, financial advice
expert systems are still relevant today.

How Does an Expert System Actually Work?

Every expert system has three core components:

1. Knowledge Base
This is where the expert's knowledge lives.
Rules written in IF-THEN format.

Example:
IF patient has fever AND cough
THEN possible diagnosis is flu

IF patient has fever AND rash
THEN possible diagnosis is measles

The more rules the more intelligent the system appears.

2. Inference Engine
This is the brain of the system.
It takes your input,matches it against rules in the knowledge base,and draws conclusions.

Two ways it reasons:

Forward chaining — starts from facts, works toward conclusion
Backward chaining — starts from conclusion, works backward to verify facts

3. User Interface
How the user interacts with the system.Usually a question and answer format.

Famous Expert Systems You Should Know

MYCIN — 1970s, Stanford University
Medical expert system for diagnosing bacterial infections and recommending antibiotics.

Built by Edward Shortliffe as part of his PhD research.
Yes one person started this.

MYCIN performed as well as human specialists in controlled tests.
It was never used clinically due to legal and ethical concerns
but it proved expert systems worked.

DENDRAL — 1965, Stanford University
First ever expert system.
Used to identify chemical compounds from mass spectrometry data.Built by a team including Edward Feigenbaum and Nobel Prize winner Joshua Lederberg.

XCON — 1980s, Digital Equipment Corporation Configured computer systems for customers.Saved DEC millions of dollars annually.
Built by a team but maintained and expanded by knowledge engineers over time.

Deep Blue — IBM
Chess playing expert system that defeated world champion Garry Kasparov in 1997.Not pure machine learning rules, evaluations, and chess expertise encoded by human grandmasters.

Can One Person Build an Expert System?

Yes. Absolutely.

MYCIN started as one person's research.Many academic expert of systems are built by individual students.

What one person needs:

Domain knowledge
Either you are the expert or you interview experts and encode their knowledge into rules.

A knowledge representation method
IF-THEN rules are the simplest.
Decision trees work too.Prolog is a programming language specifically designed for this.

An inference engine
You can build a simple one in Python.Or use existing tools like:

CLIPS — free, specifically for expert systems
Prolog — logic programming language
Jess — Java based rule engine
Experta — Python library for expert systems

A user interface
Even a simple command line Q&A works.Web interface makes it more presentable.

How to Build a Simple Expert System

Step 1 — Choose a specific domain
Not "medical diagnosis in general."
Something specific like
"diagnosing common plant diseases"or "recommending a career path for students"

Step 2 — Gather knowledge
Interview an expert OR research thoroughly.Write down every rule you can find.

Step 3 — Structure your rules
IF [condition] THEN [conclusion]
IF [condition1] AND [condition2] THEN [conclusion]

Step 4 — Choose your tool
For beginners Python with Experta library
For academic projects CLIPS
For logic focused approach Prolog

Step 5 — Build the inference engine
Match user input against your rules.Return the conclusion with confidence level.

Step 6 — Build the interface
Simple input/output to start.
Web interface to make it presentable.

Project and Research Paper Ideas

Projects:

Plant disease diagnosis expert system
Career guidance system for students
Loan eligibility assessment system
Crop recommendation system for farmers
Troubleshooting system for common software errors

Research Paper Topics:

Expert systems vs machine learning for medical diagnosis accuracy
Knowledge acquisition bottleneck in expert system development
Hybrid expert systems combining rule based and ML approaches
Expert systems for financial fraud detection
Implementing expert systems in resource limited environments

Final Thoughts

Expert systems existed before neural networks.
Before deep learning. Before ChatGPT.

They solved real problems with human knowledge encoded into rules and they worked remarkably well.

Understanding expert systems gives you a foundation for understanding how AI reasoning works at its core.

Before AI learned from data humans had to teach it everything manually.

That process capturing human expertise and encoding it into a systemis still one of the most fascinating challenges in computer science.

And yes one curious student with
a laptop and Python can absolutely build one. 😊

Have you studied expert systems in your curriculum?
Or have you built one for a project?

Drop it in the comments 👇
Would love to see what domains
students are exploring!

Green Flags & Red Flags in Fresher Job Offers : Learned the Hard Way

Anushka Shinde — Thu, 21 May 2026 04:03:52 +0000

I Applied Everywhere. Here's What I Learned.

As a fresher I was overconfident.

Two projects. Two certificates.
Applied everywhere thinking
"I've done something. Someone will notice."

Some did. Most didn't.And the ones that did weren't always the ones worth joining.

Here's everything I learned the hard way.

The Offers That Felt Wrong

The HR Recruiter Role
I applied. They called.They were impressed by how I spoke.They wanted me as an HR recruiter.

I'm a developer.I spent years learning tech.And someone wanted me to leave that because I speak well?

A good interview skill is not a reason to abandon your career path.

The Trainer Roles - Hyderabad & Bangalore
Two different cities. Same pattern.Low stipend. No real learning.Far from home. No support.

One paid so little that surviving
on my own would have meant losing money every month not gaining experience.

Moving to a new city as a fresher
with no support and no real growth?That's not an opportunity.
That's a trap dressed as one.

The Ghost Company
Got a mail. Looked genuine.From a real job portal.Mentioned a stipend. Gave a date.

I prepared. I waited. I got excited.

They never called.Never replied to my mails.Never picked up the phone.

That silence taught me something important excitement about an opportunity means nothing until it's confirmed with an actual interview.

The Red Flags I Now Recognize Immediately

🚩 They disclose a fixed amount too early
"We will pay you exactly X."
Before any interview. Before knowing you.Before understanding your skills.

Real companies don't do this.
Real companies assess first, offer later.Anyone promising money before meeting you is either wasting your time or scamming you.

🚩 The role has nothing to do with your skills
If you're a developer and they want an HR recruiter, a sales person, or a trainer that's not a career opportunity.That's just filling a seat.

🚩 No interview. No technical round.
A company that selects you without understanding what you know doesn't actually value what you know.

🚩 Location with no support
Moving cities as a fresher is fine if the opportunity is worth it.Low stipend + new city + no support network =starting your career at a loss.

🚩 They go silent after showing interest
Genuine companies follow up.
They respect your time.If they ghost you after promising an interview they were never serious.

The Green Flags That Made Me Feel Safe

✅ They wanted to know what I actually know
My genuine interview experience was simple.

They checked my resume.They asked about my projects.They asked about my tech stack.They did a proper technical round.Then an HR round.

No shortcuts. No shortcuts.They wanted to understand me before making any decision.

✅ They didn't disclose salary immediately
They said "Join us. Understand the work. If it feels right then we discuss."

That felt honest.They weren't buying me with a number.They were showing me what the work was first.

✅ They matched my tech stack
They didn't ask me to learn
something completely new from scratch.They saw what I knew and found a place where that knowledge was useful.

✅ Small company. Real work.
Not a big name. Not a famous brand.But real projects. Real learning.Real people who knew my background and chose me anyway.

That matters more than a logo.

What I'd Tell Every Fresher Right Now

1. Research the company before applying
Google them. Check LinkedIn.
Find their actual product or service.If you can't find proof they exist , don't apply.

2. Apply on genuine platforms only
LinkedIn. Internshala. Naukri.
Not random WhatsApp forwards.
Not emails from unknown addresses.

3. Don't apply everywhere
I did this. It wastes time and energy.Apply where your tech stack matches.Quality applications beat quantity every time.

4. A real company wants to assess you
No interview = no genuine interest.If they're offering without meeting you be suspicious.

5. Don't abandon your field for any offer
Just because someone is impressed
by how you speak doesn't mean you should become an HR recruiter.

You worked hard to build your skills.Don't trade them for the first call that comes.

The Honest Truth

Fresher job hunting is exhausting.Rejections feel personal even when they aren't.
Ghosting feels worse than rejection.And bad offers feel like the only options when nothing else is coming.

But one genuine opportunity one company that actually interviews you,actually assesses your skills,actually respects what you've built .

Is worth waiting for.

Don't settle for less just because the wait feels long. 😊

What's the biggest red flag YOU'VE seen in a fresher job offer?

Drop it in the comments 👇
Let's warn each other about the patterns that waste our time!

Dear CS Curriculum - It's Time for an Upgrade

Anushka Shinde — Wed, 20 May 2026 04:19:48 +0000

Let Me Say What Every CS Student Is Thinking

We learn Java.
We learn Python.
We learn C++.

And then we graduate not knowing how any of them connect to a real project.

Not knowing what a framework is
until we Google it ourselves.
Not knowing deployment exists
until an interviewer asks about it.

Something is seriously wrong here.

We Learn Languages. Not How to Use Them.

Every programming language has a purpose.Every language has frameworks built on top of it.
Every framework is used to build real things.

But our curriculum teaches us the language and stops right there.

Java taught.Spring Boot never mentioned.How Java is used to build actual web applications complete mystery.

Basic programming knowledge is important.Absolutely.But it should be a foundation not the entire building.

Doctors Update Their Syllabus. Why Don't We?

Think about this.

Medical students MBBS, doctors
their syllabus updates every time
a new medicine is approved,a new diagnosis method is established,
a new treatment protocol is introduced.

Because outdated medical knowledge can cost lives.

But in tech outdated knowledge costs careers.And somehow that's acceptable?

A technology introduced three years ago is already in every job description.But it won't enter our syllabus for another five years.

Every year the syllabus must update.Not every decade. Every year.

Our Exams Test Memory. Not Thinking.

"Define cloud computing."
"Write the definition of blockchain."
"What is the full form of API?"

These questions test nothing.

Real tech work is never about definitions.
It's about application.
It's about solving problems.
It's about building something that works.

Our papers should be application based not definition based.

Give students a problem.Ask them to design a solution.Ask them to write code that actually runs.
Ask them why they made certain decisions.

THAT tests real understanding.

We Are Stuck Between Frontend, Backend and Database

And there is SO much more to our field.

IoT. Blockchain. Serverless Computing.Edge Computing. AI and ML integration.DevOps. Cloud Architecture. Cybersecurity.

But what do most academic projects look like?

A management system.Frontend. Backend. Database.Same structure. Every semester. Every year.

Not because students aren't creative because the curriculum doesn't give them enough foundation to go beyond it.

If students knew IoT basics they'd build smart systems.
If students understood Blockchain
they'd build decentralized applications.If students learned cloud deployment their projects would actually be live.

We are capable of more.The curriculum just never showed us the door.

Deployment Exists. Please Teach It.

Development is taught.Testing is barely mentioned.Deployment completely ignored.

But what happens to a project
after it's built?

It needs to go somewhere.It needs to run on something other than localhost.It needs to be accessible to real users.

Why does our education stop at development?The software lifecycle doesn't.

Deployment. Monitoring. Scaling. Maintenance.These are real phases of real software.Students deserve to know they exist.

This Is For YouTube Too

YouTube tutorial creators you are doing incredible work for self learners everywhere.

But please update your content.

A tutorial from 4 years ago
teaching a framework version
that's been deprecated twice
is not helping anyone.

Students are learning outdated approaches because that's what shows up first in search results.

New tutorial. New version. New approach.That's what students actually need right now.

What Should Actually Change

Teach languages AND their frameworks together
Show how technologies connect in real projects
Update syllabus every single year
Make exams application based not definition based
Include deployment and later phases
Introduce IoT, Blockchain, Cloud as concepts not just buzzwords
Encourage risky, creative, unique projects
Stop rewarding management systems and start rewarding real innovation

Final Thoughts

We are not asking for too much.

We are asking to be taught things
that are actually relevant to the industry we are entering.

We are asking for a curriculum
that respects how fast our field moves.

We are asking to be treated as
future professionals not just students memorizing definitions
for an exam we'll forget next week.

The gap between what colleges teach and what companies need
is not a student problem.

It's a system problem.

And it's time the system caught up. 😊

Are you a CS student who feels this gap?
Or are you a teacher or professional who sees this from the other side?

Drop your honest thoughts below 👇
This conversation needs to happen.

7 Free Tools That Actually Helped Me as a CS Student : No Paid Subscriptions

Anushka Shinde — Tue, 19 May 2026 04:08:38 +0000

Let Me Save You Some Time

As a CS student I have tried a lot of tools.Paid ones. Free ones. Overhyped ones.

Here are the ones that actually stayed.All free. All genuinely useful.No sponsored recommendations. Just honest ones.

1. Instagram. Yes, Really

Not for reels. Not for influencers.

For developers who share:

New technologies as they happen
Real industry updates
Honest career experiences
Things that aren't in any textbook yet

When Silicon Valley announces something the right Instagram accounts talk about it the same day.

No article. No YouTube video.Just a developer who works in the industry telling you what's actually happening.

Follow the right people and your feed becomes your daily tech news. 📱

2. GitHub

Not just for storing code.

GitHub is your live portfolio.
Every project you push tells a recruiter this person actually builds things.

I learned this the hard way my first upload was a complete mess.
Files dumped flat. No folder structure.A senior developer called it out publicly.

That experience taught me more about GitHub than any tutorial did.

Push your projects. Even the messy ones.Fix them as you learn. 😊

3. Overleaf

Making a resume used to stress me out.

Word documents that break formatting.Templates that don't look professional.ATS systems that can't read fancy designs.

Overleaf changed that completely.

It's a free LaTeX editor you pick a clean professional template, fill in your details,and get a perfectly formatted PDF resume
that ATS systems actually read properly.

Perfect for beginners who don't know LaTeX the templates do the hard work for you.

4. Claude AI : For Almost Everything

I'll be completely honest Claude is my most used tool as a student.

Not because it writes things for me.Because it writes things properly.

Reports. Assignments. PPTs. Project code.Explanations that actually make sense.

The difference I noticed between AI tools:
Claude gives precise, well structured, honest answers.
It doesn't cut corners.It doesn't give you something that looks right but breaks when you test it.

For academic work especially
the quality difference is real.

5. ChatGPT : For Learning and Explaining

My workflow with ChatGPT is specific:
"I want to learn these topics one by one.Don't move to the next topic until I say I understand this one."

Then I ask questions until it clicks.

ChatGPT as a patient teacher who never gets tired of your questions that's where it shines.

Also image generation when you need a quick visual for a presentation or project diagram. 🎨

6. Consensus AI : For Research Papers

This one is underrated and I don't see enough students talking about it.

Consensus AI searches through actual research papers and gives you evidence-based answers.

I uploaded 10 to 18 research papers as references and it helped me build an original research paper idea from them.

Not copied. Not summarized. A genuinely new angle built on
existing research.

For anyone doing academic research this tool is a game changer.

7. YouTube : But Only at the Beginning

I'll be honest about YouTube too.

It's incredible for beginners.
When you know nothing about a technology a good YouTube tutorial makes it click fast.

But here's the problem most tutorials are 3 to 4 years old.
By the time you know enough to need advanced content YouTube stops being enough.

The teaching style also matters.
If you don't connect with how someone explains things no amount of rewatching helps.

Use YouTube to get started.
Then move to documentation, AI tools, and real projects to go deeper.

The Honest Rule I Follow

If it costs money I don't use it.

As a student every rupee matters.
And honestly? The free tools have
covered everything I needed so far.

The best resources aren't always
the paid ones.Sometimes they're an Instagram account,a free AI tool, or a platform that's been free since day one.

Still Looking

I'm still open to new free tools.
If something genuinely helped you
drop it in the comments.

Not affiliate links.Not "free trial" tools.Actually free. Actually useful.

Because somewhere a student is reading this who can't afford paid subscriptions but deserves the same quality resources. 😊

What free tool has genuinely helped you the most as a student?

Drop it below 👇
Let's build the most honest free
resource list on DEV.to!

How I Went From Copying Projects to Building Full Stack Apps , My Honest Journey

Anushka Shinde — Sun, 17 May 2026 04:13:25 +0000

Year One - No Projects, No Pressure

My first year was comfortable. Just learning programming languages.
No projects. No pressure.

I had no idea what was coming.

Year Two Hit Differently

Suddenly - projects.

Announced just two to three months before submission.
No real guidance on how to build one.No idea where to start.

ChatGPT existed but wasn't reliable yet.The responses were basic. Full of errors.More confusing than helpful sometimes.

So I did what made sense at that moment , I copied.

Not someone's actual code.
But the idea. The structure. The flow.I mimicked real projects. Made dummy versions.Watched YouTube tutorials and rebuilt
what I saw.

That was my starting point.And I'm not ashamed of it.Everyone starts somewhere.

The Course That Changed Everything

My college provided a free Full Stack Java Development course.

That's where I first touched:

Core Java and Advanced Java
Spring Boot
Angular
Hibernate
MySQL

But here's the problem everything was taught individually.

Spring Boot alone.Angular alone.
MySQL alone.

Nobody showed us how they connect.Nobody showed us how to build an actual application using all of them together.

We had to figure that out ourselves.

Building My First Real Project — E-Medical System

Our team decided to build an E-Medical Management System.

But before writing a single line of code we went outside.

Literally.

We visited medical shops in our hometown.Small ones. Big ones.
We talked to shop owners about what kind of system they actually needed.

What we found was interesting:

Small shops had no system at all , everything was manual
Bigger shops had systems so complicated that only young, tech-savvy people could use them
Middle-aged shop owners were completely lost with complex interfaces

So we gathered real requirements from a real small shop owner.
Built something that actually solved a real problem.

That research changed how I think
about projects forever.

How We Actually Built It

We had learned Angular and Spring Boot individually with no idea how they connected in a real application.

So here's what we did:

Designed every page on paper first
Built the frontend in Angular with help from ChatGPT
Gave that frontend code to ChatGPT and asked it to generate matching Spring Boot APIs
Connected both
Used Postman to test if APIs were working correctly
Database was designed around only the data we actually needed nothing extra

It was messy. It was frustrating.
But it worked.And we built it ourselves even if AI helped us connect the dots.

Project After Project Getting Better

After E-Medical I kept building.

A Quiz App.
A Restaurant Management System.
More full stack projects each one
better than the last.

Each project taught me something the previous one didn't.

Each mistake made the next project cleaner.Each frustration made me a better debugger.

And then came LifeFlow
my Blood Bank Management System.
Built completely solo. In PHP and MySQL.The project I'm most proud of.

If you want to read about that one I've already written about it here on DEV.to 😊

Where I Am Now

I'm not just building projects anymore.

I'm learning cloud
AWS, Azure, Google Cloud.
Understanding how applications don't just run on laptops but scale in the real world.

The journey went from:
Copying projects → Mimicking tutorials → Building with AI help → Building solo →Now learning how to deploy and scale.

What I Want You To Take From This

If you're a CS student right now
feeling lost about projects

Start by copying. That's okay.
Then start mimicking. That's progress.Then start adding your own ideas. That's growth.Then go talk to real people about real problems. That's when it gets serious.

You don't need to know everything
before you start.

You just need to start.

The rest figures itself out one frustrating, confusing,
surprisingly satisfying project at a time. 😊

Where are you in your project journey
right now?

Just starting? Already building?
Somewhere in between?

Drop it in the comments —
I'd love to know 👇

DevOps & CI/CD - What Every CS Student Should Know Before Their First Job

Anushka Shinde — Sat, 16 May 2026 09:06:13 +0000

I Thought DevOps Was Someone Else's Problem

When I first heard DevOps I thought it was something only big companies with dedicated teams worried about.

Not a student. Not a fresher.
Not someone just trying to build projects and get a job.

I was wrong.

What Even Is DevOps?

DevOps is not a tool.It's not a role exactly.It's a culture — a way of working where development and operations teams work
together continuously instead of separately.

The goal:

Build faster
Test automatically
Deploy reliably
Fix issues quickly

Traditional approach:
Developers write code → throw it to operations team → operations team figures out deployment →
something breaks → blame each other.

DevOps approach:
Everyone owns the entire lifecycle.Code → Test → Deploy → Monitor → Repeat.Continuously. Automatically.

What Is CI/CD?

CI/CD is the backbone of DevOps.

CI — Continuous Integration
Every time a developer pushes code it automatically gets:

Built
Tested
Checked for errors

No manual testing. No "works on my machine."If something breaks you know immediately.

CD — Continuous Delivery/DeploymentAfter CI passes code is automatically delivered to a staging or production environment.

No manual deployment steps.No waiting for someone to "push to server."Just push code, tests pass, live. Done.

The Tools You Should Know

Version Control

Git — non negotiable
GitHub / GitLab / Bitbucket

CI/CD Platforms

GitHub Actions — easiest to start with
Jenkins — most widely used in industry
GitLab CI — powerful and free
CircleCI

Containerization

Docker — package your app with everything it needs to run anywhere

Orchestration

Kubernetes — manage multiple containers at scale

Cloud Deployment

AWS, Azure, Google Cloud

Where I Actually Started — GitHub

Honestly?
My DevOps journey started with just GitHub.

During my internship in office we used Git workflows every single day.

Feature branches. Pull requests. Code reviews.Merging. Resolving conflicts.

That IS DevOps thinking.Not the fancy tools the discipline of
managing code collaboratively and carefully.

If you're using GitHub properly —
you're already thinking like a DevOps engineer.You just don't know it yet.

Why Students Should Care About This

Every company you interview at uses some form of CI/CD.

Even small startups.Even non-tech companies with tech teams.

When they ask "have you worked with any DevOps tools?"

GitHub is a valid answer.Git workflows are a valid answer.
Understanding why CI/CD matters is a valid answer.

You don't need to be a DevOps engineer.You need to understand the concept well enough
to work within a team that uses it.

How to Start as a Student

Step 1 — Master Git properly
Not just add, commit, push.
Learn branching, merging, pull requests,resolving conflicts.
This alone puts you ahead of most freshers.

Step 2 — Set up GitHub ActionsGitHub Actions is free for public repos.Create a simple workflow that runs your tests automatically every time you push.Takes 30 minutes to set up.
Looks impressive on your resume.

Step 3 — Dockerize one projectTake any existing project.Write a Dockerfile for it.Run it in a container.Suddenly your project runs anywhere not just your laptop with XAMPP.

Step 4 — Deploy something
Use AWS Free Tier, Render, or Railway to deploy one project publicly.A live link on your resume beats a GitHub repo every single time.

For Research Papers

Topics worth exploring:

CI/CD pipeline optimization for microservices architecture
DevOps adoption challenges in small and medium enterprises
Automated testing strategies in continuous integration pipelines
Security integration in CI/CD — DevSecOps
Containerization impact on deployment frequency and failure rates

Final Thoughts

DevOps felt overwhelming to me at first.

Too many tools. Too many concepts.Too many things I didn't know.

But then I realized , I was already doing parts of it.Git. GitHub. Collaborative workflows.
Thinking about how code gets from my laptop to somewhere real.

That's where DevOps starts.Not with Kubernetes.Not with Jenkins pipelines.With the discipline of writing code that works beyond your own machine.

Start where you are.Use what you have.GitHub is enough to begin. 😊

Are you using any DevOps tools in your projects or internship?

Or are you just starting with Git like I did?Drop your experience below 👇
And if you have a resource that made CI/CD click for you share it!
Someone reading this needs it right now 🙌