function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

function initSystem() {
  const kernel = new Core({
    threads: 16,
    memory: '64GB',
    architecture: 'x86_64'
  });
  
  kernel.boot().then(() => {
    console.log('System online.');
    startServices();
  });
}

class NeuralNet {
  constructor(layers) {
    this.layers = layers;
    this.weights = this.initializeWeights();
  }
  
  forward(inputs) {
    let current = inputs;
    for (const layer of this.layers) {
      current = layer.activate(current, this.weights);
    }
    return current;
  }
}

Full Stack Web Developer | AI Enthusiast

SHIVANSH SHARMA

I build modern full stack web applications with scalable APIs, polished user experiences, and practical AI-powered features.

View ProjectsLet's Talk

/ Philosophy

"Great software stays calm under pressure: clear architecture, reliable behavior, and code that remains easy to evolve."

I am a full stack web developer who builds complete products end to end, from responsive frontend experiences to robust backend services and databases.

As an AI enthusiast, I enjoy integrating intelligent features into real-world apps while keeping performance, usability, and maintainability at the center.

Download Resume
05+Production Projects
10+Core Technologies
1k+Concurrent Msgs/Sec
05+Open Source PRs

/ Work

Selected Artifacts

Evalio - Ai Mock Interview Platform
NODE.JSEXPRESSMONGODBREACTJWTOPENAIDEEPGRAM

Evalio - Ai Mock Interview Platform

AI-powered mock interview platform that generates personalized interview questions based on a user’s resume and target role

Study Case
Ecommerce Hybrid Automation Framework
C#SELENIUMNUNITRESTSHARP.NETGITHUB ACTIONS

Ecommerce Hybrid Automation Framework

Hybrid QA automation framework combining UI (Selenium) and API (RestSharp) testing for end-to-end validation

Study Case
LoopIn - Social Media Chat
NODE.JSFIREBASENEXT.JSPOSTGRESQLCLOUDINARY

LoopIn - Social Media Chat

Real-time chat platform built for high-concurrency communication.

Study Case
Flux Forms - Dynamic Generator
REACTNODE.JSMONGODBGEMINI API

Flux Forms - Dynamic Generator

AI-assisted form builder with a modular API architecture.

Study Case
Battle Arena - Tournament Platform
NODE.JSEXPRESSMONGODBREACT

Battle Arena - Tournament Platform

Tournament platform powered by secure, performance-focused APIs.

Study Case

/ Capabilities

Applied AI for Production

I treat AI as product infrastructure, not a demo feature. My focus is building systems that combine model capability with strong validation, predictable behavior, and measurable business outcomes.

SAP Certified Generative AI

Certified in enterprise-ready Generative AI development by SAP.

API Integration

Production integrations with safe prompts, fallbacks, and strict error handling.

Intelligent Workflows

Designing AI-backed workflows with validation, guardrails, and automation.

/ Technical Toolkit

Instruments of Choice

Node.js

Async Programming - REST APIs

Express.js

Middleware - Routing

MongoDB

Schema Design - Indexing

TypeScript

Strict typing - Scalable architecture

React.js

Component-driven UI

PostgreSQL

Relational data - SQL

Firebase

WebSockets - Real-time

Docker

Containerization

C++

High performance - Systems

C#

.NET Framework

Git

Version Control - CI/CD

JWT & RBAC

Authentication - Security

/ Journey

Feb 2026

SAP Certified Generative AI Developer

SAP

Completed enterprise-focused certification in Generative AI development and integration.

Oct 2025

Software Engineering Virtual Experience

J.P. Morgan

Built financial data modeling and visualization workflows with performance-focused engineering practices.

Jul 2025

Open Source Contributor

GSSoC'25 & Hacktoberfest

Contributed code and documentation across open-source projects, strengthening collaboration and delivery quality.

2022 - Present

B.Tech Computer Science & Engineering

Lovely Professional University

CGPA: 7.75. Ranked in the Top 10 of a college Web-A-Thon after delivering a SaaS product prototype.

/ Blog

Latest Dispatches

Thoughts on building production systems, shipping AI features, and engineering lessons from the trenches.

Mar 2026
8 min read

How URL Shorteners Work: The System Design Behind TinyURL and Bitly

A deep dive into the system design, architecture, and algorithms behind URL shortening services like TinyURL and Bitly, exploring base62 encoding, database choices, and scaling strategies.

SYSTEM DESIGNBACKENDARCHITECTURE
MAR 2026
6 min read

Caching Explained with Real Examples: The Secret Behind Fast Systems

A deep dive into caching strategies, including Cache-Aside, Write-Through, and Write-Back, explaining how real-world systems use Redis and CDNs to achieve high performance.

SYSTEM DESIGNCACHINGREDIS

Contact

Open to full stack web development and AI-focused opportunities where I can build impactful, production-ready products.

Emailshivanshsharma2704@gmail.com
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