DEV Community: Mobeen ul Hassan Hashmi

What is the Post Important things while Integrating APIs?

Mobeen ul Hassan Hashmi — Sat, 10 Jan 2026 12:42:42 +0000

🚀 Roast My Portfolio: I Launched mobeenfolio.com (Built with React & Firebase) long time ago.

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 11:59:38 +0000

Hey Dev.to family! 👋

I finally did it. After weeks of tweaking pixels, fighting with CSS alignment, and configuring Firestore rules, I have officially launched my personal portfolio:

👉 mobeenfolio.com

I am putting this out here because I know this community gives the best (and most honest) feedback. Whether it's a UI suggestion, a bug you found on mobile, or just a code optimization tip—I want to hear it.

🛠️ The Tech Stack

I wanted to build something fast, scalable, and easy to maintain. I chose the "Serverless" route:

Frontend: React (for that snappy component-based architecture)
Styling: Tailwind CSS (because writing custom CSS files is so 2020)
Backend & Database: Firebase (Firestore for data, Hosting for deployment)
Icons: React Icons

🧩 A Cool Code Snippet

One thing I love about this stack is how clean the component logic gets when you combine Tailwind utility classes with React state.

Check out this

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 11:40:09 +0000

The Death of the Syntax Coder: How AI Will Transform Your Career in 2026 (and How to Survive) - DEV Community

If you’ve been on Twitter/X lately, you’ve seen the doom-scrolling posts: "Devin just built my...

dev.to

The Death of the Syntax Coder: How AI Will Transform Your Career in 2026 (and How to Survive)

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 11:39:41 +0000

If you’ve been on Twitter/X lately, you’ve seen the doom-scrolling posts: "Devin just built my startup in 4 minutes," or "ChatGPT-5 writes better SQL than I do."

It is easy to panic. It is easy to think the Golden Age of Software Engineering is over.

But if we look at the trajectory of our industry, the reality for 2026 and beyond is much more nuanced. The role of the "Full-Stack Developer" is not dying—it is molting. We are shedding the skin of "Syntax Typists" to reveal our new form: System Architects and AI Orchestrators.

This is your career roadmap for the next 5 years. This is how you stay relevant, valuable, and highly paid in the age of AI.

The Reality Check: 2026 vs. 2023

To understand where we are going, we have to look at what we are losing.

💀 What is Dying?

Boilerplate Coding: Manually typing out divs, setting up Express servers from scratch, and writing basic CRUD reducers.
Syntax Memorization: Being a "dictionary" of CSS grid properties or RegEx patterns.
The "Junior" Ticket: Simple tasks like "Change the button color" or "Fix this typo" are now automated by agents before they even reach a human's backlog.

🚀 What is Exploding?

System Architecture: Knowing how the frontend, backend, and AI agents talk to each other.
Code Review & Auditing: The ability to look at AI-generated code and instantly spot security vulnerabilities or logic flaws.
"Vibe Coding" (Intent-Based Programming): Using natural language to describe complex logic and having the machine compile it into execution.

"It is our job to create computing technology such that nobody has to program. And that the programming language is human."

— Jensen Huang, CEO of NVIDIA

The New Workflow: "Vibe Coding" & Agent Orchestration

In 2023, if you wanted to build a feature, you wrote the code.
In 2026, you orchestrate the code.

Let’s look at a concrete example of how a Full-Stack Developer’s daily task changes.

The Task: "Build a User Dashboard showing top sales."

❌ The Old Way (Manual)

You spend 4 hours:

Creating the React component file.
Importing useEffect and useState.
Writing the API call to fetch data.
Debugging why the API call is firing twice (React.StrictMode strikes again).
Writing the CSS to make it responsive.

✅ The 2026 Way (AI Orchestration)

You spend 30 minutes. You don't "write" the code; you prompt the architecture.

Step 1: The Prompt
You type this into your IDE (VS Code with Copilot Workspace or Cursor):

"Create a sales dashboard component. It needs to fetch data from the /api/sales endpoint. Use a TanStack Query for caching. Visuals should be a bar chart using Recharts. Handle loading states and error boundaries gracefully."

Step 2: The Review (This is your REAL job now)
The AI generates 200 lines of code in 10 seconds. Now, your expertise kicks in. You are no longer the writer; you are the Editor-in-Chief.

You scan the code and spot issues the AI missed:

Security: "The API call isn't passing the Auth token in the headers." -> You fix it.
Performance: "It's re-rendering the chart on every mouse hover." -> You optimize it.
Business Logic: "The chart sums up 'gross revenue', but the PM asked for 'net profit'." -> You adjust the query.

// 2026 Workflow Example
// You didn't write this function. You reviewed it.

import { useQuery } from '@tanstack/react-query';
import { fetchSalesData } from '../api';

export function SalesDashboard() {
  // AI generated this. 
  // YOU decided to use useQuery instead of useEffect for better caching.
  const { data, isLoading, error } = useQuery({
    queryKey: ['sales'],
    queryFn: fetchSalesData,
    staleTime: 1000 * 60 * 5 // 5 minutes (Your architectural decision)
  });

  if (isLoading) return <SkeletonLoader />;
  if (error) return <ErrorBanner message={error.message} />;

  return (
    <div className="p-6 bg-white rounded-xl shadow-sm">
      <h2 className="text-2xl font-bold mb-4">Quarterly Performance</h2>
      {/* AI handles the repetitive UI libraries */}
      <SalesChart data={data} />
    </div>
  );
}

The 2026 Tech Stack: What You Need to Learn

The MERN stack (MongoDB, Express, React, Node) is still here, but it has a new layer on top: The AI Layer.

If you want to stay employable, add these to your arsenal immediately.

1. Vector Databases (The AI's Memory)

Traditional SQL databases are for facts. Vector databases (Pinecone, Weaviate, pgvector) are for context.

Why? To build apps that "chat" with your users, you need to store data as embeddings, not just strings.
Action: Learn how to implement RAG (Retrieval-Augmented Generation).

2. LLM Orchestration (LangChain / Vercel AI SDK)

You need to know how to chain prompts together.

Example: User asks a question -> App searches database -> App summarizes data -> App formats it as an email.
Action: Build a simple chatbot that can query a PDF file.

3. Verification Engineering (Testing)

When AI writes the code, testing becomes more important than ever.

You need to write rigid end-to-end tests (Playwright, Cypress) to ensure the AI didn't hallucinate a feature that doesn't exist.

The "Soft" Skills That Will Pay The Bills

As coding becomes cheaper, human judgment becomes priceless.

"AI will lead to fewer software engineers... but each software engineer will just do much, much more."

— Sam Altman, CEO of OpenAI

The developers who get paid $200k+ in 2026 will be the ones who can:

Translate Business to Tech: A Product Manager says, "I want users to feel safe." You translate that into "We need 2FA and an Audit Log." AI cannot do that translation yet.
Debug Systems, Not Just Code: When the AI agent fails, it won't throw a syntax error. It will just give a wrong answer. Tracing why it gave a wrong answer (Prompt drift? Bad data embedding?) is a massive new skill.
Empathy & UX: AI can build a UI, but it doesn't know what "frustration" feels like. You are the guardian of the user experience.

Your 5-Year Action Plan

If you are a Junior or Mid-level dev right now, here is your survival guide:

Year 1 (Now): Stop fighting tools like Copilot. Master them. Learn how to prompt effectively. Start learning Next.js or a full-stack framework that integrates easily with AI.
Year 2-3: Learn Data Engineering basics. How do you clean data so an AI can understand it? Learn Python (just enough for scripting AI workflows).
Year 4-5: Pivot your title to "Solutions Architect" or "Product Engineer". Position yourself as someone who builds products, not just features.

Conclusion

The "Code Monkey" is dead. Long live the Product Architect.

Don't let the AI hype scare you into quitting. The world will always need people who can solve problems. The tools are changing, but the mission remains the same: Building cool stuff that helps people.

The only developers who will be replaced by AI are the ones who refuse to use it.

🗣️ Discussion

Are you already using AI in your daily workflow? Does it make you feel more productive or more anxious? Let's talk in the comments below! 👇

Death of Syntax Coders

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 11:29:06 +0000

The Death of the Syntax Coder: How AI Will Transform Your Career in 2026 (and How to Survive) - Open Forem

If you’ve been on Twitter/X lately, you’ve seen the doom-scrolling posts: "Devin just built my...

open.forem.com

The Death of the Syntax Coder: How AI Will Transform Your Career in 2026 (and How to Survive)

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 11:28:29 +0000

If you’ve been on Twitter/X lately, you’ve seen the doom-scrolling posts: "Devin just built my startup in 4 minutes," or "ChatGPT-5 writes better SQL than I do."

It is easy to panic. It is easy to think the Golden Age of Software Engineering is over.

This is your career roadmap for the next 5 years. This is how you stay relevant, valuable, and highly paid in the age of AI.

The Reality Check: 2026 vs. 2023

To understand where we are going, we have to look at what we are losing.

💀 What is Dying?

Boilerplate Coding: Manually typing out divs, setting up Express servers from scratch, and writing basic CRUD reducers.
Syntax Memorization: Being a "dictionary" of CSS grid properties or RegEx patterns.
The "Junior" Ticket: Simple tasks like "Change the button color" or "Fix this typo" are now automated by agents before they even reach a human's backlog.

🚀 What is Exploding?

System Architecture: Knowing how the frontend, backend, and AI agents talk to each other.
Code Review & Auditing: The ability to look at AI-generated code and instantly spot security vulnerabilities or logic flaws.
"Vibe Coding" (Intent-Based Programming): Using natural language to describe complex logic and having the machine compile it into execution.

"It is our job to create computing technology such that nobody has to program. And that the programming language is human."

— Jensen Huang, CEO of NVIDIA

The New Workflow: "Vibe Coding" & Agent Orchestration

In 2023, if you wanted to build a feature, you wrote the code.
In 2026, you orchestrate the code.

Let’s look at a concrete example of how a Full-Stack Developer’s daily task changes.

The Task: "Build a User Dashboard showing top sales."

❌ The Old Way (Manual)

You spend 4 hours:

Creating the React component file.
Importing useEffect and useState.
Writing the API call to fetch data.
Debugging why the API call is firing twice (React.StrictMode strikes again).
Writing the CSS to make it responsive.

✅ The 2026 Way (AI Orchestration)

You spend 30 minutes. You don't "write" the code; you prompt the architecture.

Step 1: The Prompt
You type this into your IDE (VS Code with Copilot Workspace or Cursor):

"Create a sales dashboard component. It needs to fetch data from the /api/sales endpoint. Use a TanStack Query for caching. Visuals should be a bar chart using Recharts. Handle loading states and error boundaries gracefully."

Step 2: The Review (This is your REAL job now)
The AI generates 200 lines of code in 10 seconds. Now, your expertise kicks in. You are no longer the writer; you are the Editor-in-Chief.

You scan the code and spot issues the AI missed:

Security: "The API call isn't passing the Auth token in the headers." -> You fix it.
Performance: "It's re-rendering the chart on every mouse hover." -> You optimize it.
Business Logic: "The chart sums up 'gross revenue', but the PM asked for 'net profit'." -> You adjust the query.

// 2026 Workflow Example
// You didn't write this function. You reviewed it.

import { useQuery } from '@tanstack/react-query';
import { fetchSalesData } from '../api';

export function SalesDashboard() {
  // AI generated this. 
  // YOU decided to use useQuery instead of useEffect for better caching.
  const { data, isLoading, error } = useQuery({
    queryKey: ['sales'],
    queryFn: fetchSalesData,
    staleTime: 1000 * 60 * 5 // 5 minutes (Your architectural decision)
  });

  if (isLoading) return <SkeletonLoader />;
  if (error) return <ErrorBanner message={error.message} />;

  return (
    <div className="p-6 bg-white rounded-xl shadow-sm">
      <h2 className="text-2xl font-bold mb-4">Quarterly Performance</h2>
      {/* AI handles the repetitive UI libraries */}
      <SalesChart data={data} />
    </div>
  );
}

The 2026 Tech Stack: What You Need to Learn

The MERN stack (MongoDB, Express, React, Node) is still here, but it has a new layer on top: The AI Layer.

If you want to stay employable, add these to your arsenal immediately.

1. Vector Databases (The AI's Memory)

Traditional SQL databases are for facts. Vector databases (Pinecone, Weaviate, pgvector) are for context.

Why? To build apps that "chat" with your users, you need to store data as embeddings, not just strings.
Action: Learn how to implement RAG (Retrieval-Augmented Generation).

2. LLM Orchestration (LangChain / Vercel AI SDK)

You need to know how to chain prompts together.

Example: User asks a question -> App searches database -> App summarizes data -> App formats it as an email.
Action: Build a simple chatbot that can query a PDF file.

3. Verification Engineering (Testing)

When AI writes the code, testing becomes more important than ever.

You need to write rigid end-to-end tests (Playwright, Cypress) to ensure the AI didn't hallucinate a feature that doesn't exist.

The "Soft" Skills That Will Pay The Bills

As coding becomes cheaper, human judgment becomes priceless.

"AI will lead to fewer software engineers... but each software engineer will just do much, much more."

— Sam Altman, CEO of OpenAI

The developers who get paid $200k+ in 2026 will be the ones who can:

Translate Business to Tech: A Product Manager says, "I want users to feel safe." You translate that into "We need 2FA and an Audit Log." AI cannot do that translation yet.
Debug Systems, Not Just Code: When the AI agent fails, it won't throw a syntax error. It will just give a wrong answer. Tracing why it gave a wrong answer (Prompt drift? Bad data embedding?) is a massive new skill.
Empathy & UX: AI can build a UI, but it doesn't know what "frustration" feels like. You are the guardian of the user experience.

Your 5-Year Action Plan

If you are a Junior or Mid-level dev right now, here is your survival guide:

Year 1 (Now): Stop fighting tools like Copilot. Master them. Learn how to prompt effectively. Start learning Next.js or a full-stack framework that integrates easily with AI.
Year 2-3: Learn Data Engineering basics. How do you clean data so an AI can understand it? Learn Python (just enough for scripting AI workflows).
Year 4-5: Pivot your title to "Solutions Architect" or "Product Engineer". Position yourself as someone who builds products, not just features.

Conclusion

The "Code Monkey" is dead. Long live the Product Architect.

The only developers who will be replaced by AI are the ones who refuse to use it.

🗣️ Discussion

Are you already using AI in your daily workflow? Does it make you feel more productive or more anxious? Let's talk in the comments below! 👇

Fixing Real-Time Notification Issues Using Vue, Laravel, and Socket.IO

Mobeen ul Hassan Hashmi — Sun, 04 Jan 2026 10:39:01 +0000

Real-time notifications are a core feature in many modern applications.

Recently, while working on a Vue + Laravel application, I faced multiple issues with Socket.IO-based notifications that worked fine locally but caused problems in production.

In this post, I’ll explain what went wrong, how I fixed it, and the lessons I learned.

🔔 The Problem

We implemented real-time notifications using Socket.IO so users could instantly receive updates (events, alerts, system messages).

Issues we faced:

Notifications randomly stopped arriving
Duplicate notifications after page refresh
Users stayed “connected” but didn’t receive messages
Everything worked locally, but production was unstable

This caused confusion and reduced trust in the system.

🧰 Tech Stack

Frontend: Vue.js
Backend: Laravel
WebSocket: Socket.IO
Auth: Token-based authentication
Server: Nginx + Production environment

🔍 Root Cause Analysis

After debugging both frontend and backend, the main issues were:

WebSocket connections were created multiple times
Event listeners were not cleaned up
Users were not mapped correctly to socket connections
Idle connections were silently dropped
Reconnection logic caused duplicate events

In short:

👉 The WebSocket connection existed, but it wasn’t managed properly.

🛠️ The Solution

1️⃣ Proper Socket Initialization in Vue

The socket was being re-initialized on every component load.

Fix: Create a single reusable socket instance.


js
// socket.js
import { io } from "socket.io-client";

let socket = null;

export const connectSocket = (token) => {
  if (!socket) {
    socket = io(import.meta.env.VITE_SOCKET_URL, {
      auth: { token },
      transports: ["websocket"],
    });
  }
  return socket;
};