DEV Community: Ajeet Verma

About Ajeet Verma | Java Backend Developer | Spring Boot | Spring AI | Software Engineer

Ajeet Verma — Thu, 06 Aug 2026 11:20:06 +0000

If you searched for Ajeet Verma or ajeetverma01, welcome!
I'm Ajeet Verma, a Java Backend Developer passionate about building scalable enterprise applications, secure REST APIs, AI-powered solutions, and modern backend systems.
This page serves as the central hub for my technical work, projects, articles, and professional profiles across the web. Whether you're a recruiter, developer, student, or technology enthusiast, you'll find everything about my work here.

Who is Ajeet Verma?

I'm a software developer with a strong interest in backend engineering, enterprise software, and Artificial Intelligence.
My primary expertise lies in the Java ecosystem, where I build secure, scalable, and production-ready applications using modern frameworks and best engineering practices.
Beyond writing code, I enjoy understanding how technologies work under the hood and sharing that knowledge through technical writing.
This DEV profile is where I publish articles covering backend development, software engineering, Java, Spring Boot, AI, system design, Docker, and emerging technologies.

My Tech Stack

Backend

Java
Spring Boot
Spring Security
Spring AI
Hibernate / JPA
REST APIs
JWT Authentication

Frontend

React
JavaScript
HTML
CSS

Databases

PostgreSQL
MySQL

DevOps & Tools

Docker
Git
GitHub
Maven
IntelliJ IDEA
VS Code

Artificial Intelligence

Spring AI
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
AI Agents
Model Context Protocol (MCP )

What I Build

I enjoy building projects that solve real-world problems while following modern software engineering principles.

Some areas I frequently work on include:

Enterprise Backend Applications
Secure Authentication Systems
RESTful APIs
AI-powered Applications
Spring AI Projects
Dockerized Applications
Full-Stack Web Applications
Software Architecture
Intelligent Automation

Every project helps me improve my understanding of scalable software development and modern backend technologies.

What You'll Find on This Blog

This blog focuses on practical software engineering and enterprise development.
Topics you'll regularly see include:

Java
Spring Boot
Spring AI
Backend Development
Docker
System Design
Authentication & Authorization
Software Architecture
Artificial Intelligence
Generative AI
Large Language Models
Microservices
Cloud Technologies
Developer Productivity
Project Walkthroughs

My goal is to explain technical concepts in a practical, beginner-friendly, and industry-focused way.
Featured Projects
Some of the projects I've built include:

JWT Authentication System using Spring Boot & React
Expense & Income Tracker
Portfolio Website
Smart Shop Manager
Library Management System
College Management System

More projects are continuously being added to my GitHub.

Connect With Me

Portfolio
GitHub
LinkedIn
DEV Community
LeetCode
HackerRank
Fiverr
Instagram
Threads
Facebook
YouTube

Why I started writing?

Writing technical content helps me organize my thoughts, deepen my understanding, and contribute to the developer community.
Instead of simply documenting code, I enjoy explaining the ideas behind technologies—how they work, why they matter, and where they're used in real-world software development.
Through this blog, I hope to help developers learn something new while continuing to grow as an engineer myself.

Let's Build Together

If you're interested in Java, Spring Boot, Spring AI, backend engineering, software architecture, Docker, Artificial Intelligence, or simply enjoy discussing technology, feel free to connect with me.
I'm always open to learning, collaborating, and sharing ideas with fellow developers.
Thanks for visiting my profile!
— Ajeet Verma

What Really Happens When You Click "Login"?

Ajeet Verma — Thu, 06 Aug 2026 03:55:15 +0000

The journey of a login request—from your screen to secure authentication.

Every day, millions of people click the "Login" button without giving it a second thought.

It feels like a simple action that takes just a few seconds.

But behind that single click, a series of carefully orchestrated processes work together to verify your identity, protect your credentials, and grant secure access to your account.

Let's take a look at what actually happens behind the scenes.

1. You Enter Your Credentials

It all begins when you type your email (or username) and password into the login form.

Once you click Login, your browser or mobile application doesn't verify your credentials itself. Instead, it packages the information into an HTTPS request and securely sends it to the backend server.

HTTPS encrypts the data while it's traveling across the internet, ensuring that sensitive information can't be easily intercepted.

2. The Backend Receives the Request

The server receives the authentication request and begins processing it.

Before anything else, it validates the incoming data:

Are the required fields present?
Is the email formatted correctly?
Does the request meet security and validation rules?

Only after passing these checks does the authentication process continue.

3. The Server Looks Up Your Account

The backend queries the database using your email or username.

If no matching account exists, the server immediately returns an authentication failure.

If the account exists, the server retrieves the stored user information—including the hashed password, not the original password.

This is an important security principle:

Well-designed applications never store plain-text passwords.

Instead, passwords are transformed into irreversible hashes using algorithms like BCrypt or Argon2.

4. Password Verification

Many people think the server decrypts your password.

It doesn't.

The password you entered is hashed using the same algorithm and compared against the stored hash.

If both hashes match, your identity is verified.

If they don't, access is denied.

This process allows applications to verify passwords without ever knowing or storing the original password.

5. Authentication Token Is Generated

Once authentication succeeds, the server generates an authentication token.

In many modern applications, this is a JWT (JSON Web Token).

Some applications also issue:

An Access Token for API requests.

A Refresh Token to obtain new access tokens without asking users to log in again.

These tokens represent your authenticated session.

6. The Client Stores the Token
The frontend receives the token and stores it securely.

Depending on the application's architecture, it may be stored in:

HttpOnly Cookies
Secure Cookies
Browser Storage
Mobile Secure Storage

Security practices differ depending on the application's requirements.

7. Every Future Request Includes the Token

After logging in, you don't send your password with every request.

Instead, each API request includes the authentication token.

The backend validates the token before allowing access to protected resources.

If the token is valid, the request proceeds.

If the token has expired or has been tampered with, the request is rejected.

This enables modern applications to remain stateless, scalable, and secure.

Why This Matters
A login system isn't simply checking whether a password is correct.

It's establishing trust between a user and an application while protecting sensitive information at every step.

Behind a single click lies encryption, password hashing, database lookups, authentication, token generation, session management, and multiple security checks—all designed to provide a seamless and secure user experience.

The next time you click "Login," remember that your application has already completed a sophisticated authentication workflow in just a few milliseconds.

Authentication is one of those features users rarely notice—until it fails.

Which part of the login process do you find most interesting: password hashing, JWT authentication, or token-based authorization?

Why AI Hallucinates: Think of It Like a GPS with an Outdated Map

Ajeet Verma — Mon, 03 Aug 2026 03:27:28 +0000

Artificial Intelligence has become incredibly powerful, but one question continues to puzzle many people:
"Why does AI sometimes give completely wrong answers with so much confidence?"
The answer becomes much easier when you think of AI as a GPS with an outdated map.
Imagine you're driving to a destination using GPS. Most of the roads on the map are accurate, and the navigation works perfectly. But suddenly, you reach an area where the map hasn't been updated.
Instead of saying,
"I don't know this route."
the GPS calculates what it believes is the most likely path based on the available information.
It confidently tells you to turn left...
...only for you to discover that the road no longer exists.
That's remarkably similar to how AI hallucinations occur.
Large Language Models (LLMs) don't search the internet every time you ask a question, nor do they reason like humans. They generate responses by predicting the most probable sequence of words based on patterns learned from massive amounts of training data.
Most of the time, those predictions are accurate.
However, when the model encounters incomplete information, ambiguous prompts, or topics outside its knowledge, it may generate an answer that is:
✔ Grammatically correct
✔ Logically structured
✔ Highly convincing
...but factually incorrect.
This phenomenon is known as an AI hallucination.
The important thing to understand is that AI isn't intentionally making things up. It isn't trying to deceive anyone.
It's simply predicting what is most likely to come next—not verifying whether the information is actually true.
This is exactly why modern AI systems are increasingly combined with technologies such as Retrieval-Augmented Generation (RAG), tool calling, knowledge bases, and real-time search. These approaches allow AI to retrieve reliable information before generating a response, significantly reducing hallucinations and improving accuracy.
As AI becomes part of enterprise software, healthcare, finance, education, and countless other industries, understanding its limitations is just as important as understanding its capabilities.
The biggest lesson?
Confidence is not the same as correctness.
Just because an AI sounds certain doesn't mean the answer is true—just like a GPS can confidently guide you toward a road that no longer exists.
The future of AI isn't just about making models smarter.
It's about making them more reliable, verifiable, and trustworthy.

Understanding AI hallucinations isn't just important for AI engineers—it's becoming essential for every developer, business, and user interacting with AI.
As AI becomes integrated into enterprise applications, customer support, healthcare, finance, and education, the focus is no longer just on generating intelligent responses. The real challenge is ensuring those responses are accurate, trustworthy, and grounded in reliable information.
That's why modern AI systems increasingly rely on techniques such as Retrieval-Augmented Generation (RAG), tool calling, knowledge bases, and real-time data retrieval. These approaches don't just make AI smarter—they make it more dependable.
The future of AI isn't about building models that always have an answer.
It's about building systems that know when to answer, when to retrieve information, and when to say, "I don't know."
Because in AI, confidence is easy to generate—but trust has to be earned.

--By Ajeet Verma(Java full stack developer)

What analogy would you use to explain AI hallucinations to someone new to AI?

Why Docker Has Become a Standard Tool for Developers

Ajeet Verma — Fri, 31 Jul 2026 09:17:54 +0000

Modern software development is no longer just about writing code—it's about ensuring that code runs consistently across every environment.

For years, one of the biggest challenges developers faced was the classic:

«"It works on my machine."»

Docker fundamentally changed that.

By packaging an application with its runtime, dependencies, libraries, and configuration into lightweight containers, Docker ensures the application behaves the same whether it's running on a developer's laptop, a testing environment, or a production server.

Its impact goes far beyond containerization.

✔ Consistent development environments
✔ Faster onboarding for new developers
✔ Simplified dependency management
✔ Improved CI/CD pipelines
✔ Efficient resource utilization compared to traditional virtual machines
✔ Seamless deployment across cloud and on-premise infrastructure

Today, Docker has become a core part of the modern software development lifecycle. It's commonly used alongside technologies such as Kubernetes, GitHub Actions, Jenkins, and cloud platforms to build scalable, portable, and production-ready applications.

As applications continue to move toward cloud-native architectures, understanding Docker is no longer optional—it's becoming a fundamental skill for software engineers.

Docker didn't just solve deployment problems.

It standardized how modern applications are built, shipped, and deployed.

Docker #DevOps #CloudNative #SoftwareEngineering #BackendDevelopment #Java #SpringBoot #Kubernetes #CICD #Containers #DeveloperTools

Why Spring AI Could Be the Next Big Evolution of the Java Ecosystem

Ajeet Verma — Fri, 24 Jul 2026 02:57:58 +0000

Spring AI could become one of the most significant additions to the Java ecosystem in years.

The Java ecosystem has continuously evolved to meet the demands of modern software development—from enterprise applications and microservices to cloud-native architectures.

Now, the next evolution is Artificial Intelligence.

Spring AI is positioning Java to play a central role in building AI-powered enterprise applications. Rather than introducing an entirely new development model, it extends the Spring ecosystem with AI capabilities while preserving the principles that have made Spring the foundation of enterprise Java for over two decades.

This shift is important because enterprises aren't looking to replace their existing Java applications—they're looking to make them intelligent.

As organizations invest in LLMs, AI agents, RAG, and intelligent automation, frameworks that seamlessly integrate these capabilities into production systems will define the next generation of enterprise software.

Spring AI is more than a new project.

It represents the convergence of the Java ecosystem and Generative AI—bringing enterprise reliability, scalability, and developer productivity into the AI era.

The future of enterprise Java isn't just cloud-native.

It's AI-native.

SpringAI #SpringBoot #Java #JavaEcosystem #EnterpriseJava #GenerativeAI #ArtificialIntelligence #AIEngineering #SoftwareArchitecture #BackendDevelopment #LLM #Innovation

How I Built JWT Authentication in Spring Boot (Beginner-Friendly Guide)

Ajeet Verma — Thu, 23 Jul 2026 07:31:24 +0000

How I Built JWT Authentication in Spring Boot (Beginner-Friendly Guide)

Authentication is one of the first things every backend developer learns when building real-world applications.

While learning Spring Boot, I wanted to understand how secure authentication actually works, instead of simply copying code from tutorials. So I built a complete JWT Authentication system from scratch.

In this article, I'll share what I learned and how the authentication flow works.

Why JWT?

JWT (JSON Web Token) is a compact, secure way to authenticate users without storing session data on the server.

This makes applications stateless, scalable, and suitable for REST APIs.

Authentication Flow

User signs up with an email and password.
Password is securely hashed using BCrypt.
User logs in with valid credentials.
Spring Security authenticates the user.
The server generates a JWT.
The frontend stores the token.
Every protected request includes the token in the Authorization header.
A custom JWT filter validates the token before granting access.

What I Implemented

User Registration
Secure Login
Password Hashing using BCrypt
JWT Access Token Generation
Spring Security Configuration
Custom JWT Authentication Filter
Protected REST APIs
Token Validation
Exception Handling

Challenges I Faced

Like every beginner, I faced several issues:

Understanding the Spring Security filter chain
Fixing CORS errors
Handling invalid and expired tokens
Protecting APIs correctly
Learning the difference between Authentication and Authorization

Each issue helped me understand Spring Security much better.

What I Learned

Building authentication from scratch taught me much more than following tutorials.

I now have a better understanding of:

Spring Security
Stateless Authentication
JWT
BCrypt Password Encoding
REST API Security
Clean Backend Architecture

What's Next?

I'm currently building more backend projects using Spring Boot and exploring Spring AI to deepen my understanding of modern Java development.

If you have suggestions or feedback, I'd love to hear them.

Happy Coding! 🚀