Forem: Md Mijanur Molla

What Really Happens When You Call an API

Md Mijanur Molla — Wed, 22 Apr 2026 06:42:48 +0000

We use APIs every day.

Fetching user data
Sending login requests
Getting products from backend

But have you ever thought:

👉 What actually happens after you call an API?

Let’s break it down in simple, real-world steps 👇

💡 Step 1: You Trigger the Request

It starts when your code runs something like:

fetch("https://api.example.com/users")

Or using Axios, Postman, anything.

👉 This creates an HTTP request

🌐 Step 2: DNS Lookup (Finding the Server)

Before sending the request, your system asks:

👉 “Where is api.example.com?”

So it contacts a DNS server.

DNS returns:

👉 The IP address of the server

📡 Step 3: Request Travels Over the Internet

Now your request:

Goes through routers
Travels across networks
Reaches the server

👉 All this happens in milliseconds

🔐 Step 4: Secure Connection (HTTPS)

If you’re using HTTPS:

SSL/TLS handshake happens
Connection gets encrypted

👉 Your data is now secure

⚙️ Step 5: Server Receives the Request

The server gets:

URL
Method (GET, POST, etc.)
Headers
Body (if any)

Now backend logic starts.

🧠 Step 6: Backend Processes It

Server does things like:

Validate request
Authenticate user
Run business logic
Fetch data from database

👉 This is the “brain” of your app

🗄️ Step 7: Database Interaction

If needed:

Server queries database
Gets data
Processes it

Example:

👉 “Get all users” → DB returns rows

📦 Step 8: Response is Created

Server prepares response:

JSON data
Status code (200, 404, 500)
Headers

👉 Example:

{
  "users": ["A", "B", "C"]
}

🚀 Step 9: Response Travels Back

The response:

Goes back through internet
Reaches your app

👉 Again in milliseconds

💻 Step 10: Your App Uses the Data

Finally:

UI updates
Data is displayed
User sees result

👉 That’s the moment you notice

🔄 Simple Flow

👉 Request → Internet → Server → Database → Response → UI

⚠️ Why Things Go Wrong Sometimes

If any step fails:

DNS issue
Network error
Server crash
Wrong API logic

👉 You get errors like 500, 404

🎯 Real Developer Insight

Calling an API is not just one function.

👉 It’s a full journey across systems

Understanding this helps you:

Debug faster
Design better systems
Think like a backend engineer

🚀 Final Thought

Next time you write:

fetch(...)

Remember:

👉 You just triggered a multi-step process across the internet

And that’s the real beauty of software engineering 💙

I Built an “Online but Not Replying” System… And It Created Trust Issues 😭

Md Mijanur Molla — Tue, 21 Apr 2026 09:21:04 +0000

You’ve seen this.

They are Online

You send a message

…

…

No reply.

Still online.

👉 Now you’re thinking:

Are they busy? Ignoring you? Or is the system wrong?

So I turned this into a coding challenge.

And honestly… it exposed a real bug.

😂 The Problem

The logic looks simple:

User opens app → set Online
User leaves → set Offline

That’s it.

But real systems don’t behave that cleanly.

⚠️ What Goes Wrong?

In real-world apps:

• User closes the app suddenly

• Network disconnect is not detected

• “Offline” event is never sent

• System keeps showing user as Online

And suddenly:

👉 System says “Online”

👉 Reality says “Not even there” 😭

🧠 What I Observed

When I explored this:

Basic implementations depend on events
But events can fail or get lost
No timeout means stale state
No fallback means incorrect status

The code works.

But the experience?

👉 Completely misleading.

🔍 The Real Issue

This is not just about status.

It’s about:

• Real-time reliability

• State accuracy

• Handling unexpected disconnects

• System truth vs user perception

Because:

👉 “Online” should actually mean online

💡 What a Better System Needs

A proper presence system should:

Use heartbeat (regular ping from client)
Add timeout (auto mark offline)
Detect sudden disconnects
Sync state across devices

This ensures:

👉 Accurate status

👉 No confusion

👉 Better user trust

🔥 Try My Challenge

I created this as a fun (but real) system problem.

👉 Try it here:
https://vibecodearena.ai/duel/a2866d85-1697-46cd-96e8-84cb14739ae2

Can you:

Fix fake online status?
Handle disconnects properly?
Build a reliable presence system?

🎯 Final Thought

Some systems show data.

Some systems show truth.

And this one…

👉 Sometimes shows lies 😭

So tell me 👇

Are they really online… or is the system just playing games with you?

I Built a Complete Developer Hub — Introducing TechForDev

Md Mijanur Molla — Mon, 20 Apr 2026 05:00:32 +0000

If you’re a developer, you already know the struggle.

You open your laptop to learn or build something…
and within minutes, you have 10+ tabs open:

One for tech news
One for AI tools
One for APIs
One for AI models
One for jobs
One for learning roadmap
One for random Google searches

And eventually, you lose focus.

That exact problem pushed me to build something better.

Introducing TechForDev

https://techfordev.netlify.app/

TechForDev is a platform designed to bring everything a developer needs into one place.

Instead of switching between multiple platforms,
you get a centralized developer dashboard.

Core Features

1. Live Tech News (Auto-Updating)

Stay updated without manually searching.

Aggregates latest tech news from multiple sources
Covers AI, startups, software, and industry trends
Auto-refresh system (every 30 minutes)
Clean and readable layout

No more endless scrolling on random sites

2. AI Tools Directory

Discover tools that can 10x your productivity.

Curated AI tools for developers and creators
Categories like coding, writing, design, automation
Helps you explore tools you didn’t even know existed

Saves hours of research

3. Developer Roadmaps

Clear direction for learning any tech stack.

Structured paths for different domains
Beginner-friendly guidance
Helps avoid confusion and random learning

Perfect for students and self-learners

4. Job Opportunities Section

Find relevant opportunities in one place.

Curated job listings
Focus on tech roles
Saves time from jumping across job portals

Especially useful for freshers

️ 5. Free APIs Collection

Build projects faster with ready-to-use APIs.

Organized list of useful APIs
Covers different use cases
Helpful for hackathons and projects

No need to search “free API list” again and again

6. Salary Insights

Understand the market better.

Salary trends across roles
Helps in career planning
Useful before interviews or job switch

Make informed decisions

⚔️ 7. Coding Challenges

Practice and improve consistently.

Skill-based challenges
Helps build problem-solving mindset
Good for interview preparation

Learn by doing

8. Tech Comparison Tool

Confused between technologies? This helps.

Compare frameworks, languages, and tools
Simplified insights
Better decision-making support

Choose smarter, not randomly

️ 9. Podcasts & Learning Resources

Learn from real-world experiences.

Developer podcasts
Industry insights
Practical knowledge beyond tutorials

Learn what actually matters

⚡ 10. Built-in Developer Tools

Small tools that save big time.

JSON Formatter
Resume AI Tool
Other utilities

Quick access without leaving the platform

Why I Built This

The goal is simple:

Reduce distraction
Save time
Increase productivity

Instead of managing multiple tabs and platforms,
TechForDev gives you a single, clean ecosystem.

What’s Next?

This is just Version 1.

Planned improvements:

User accounts & personalization
Save/bookmark features
More AI-powered tools
Better UI/UX
Community features

Your Feedback Matters

I’m building this in public, and your feedback can shape it.

Try it out: https://techfordev.netlify.app/
Share your thoughts

What should I add next? What should I improve?

WebDevelopment #Developers #BuildInPublic #Tech #AI #Coding #SoftwareEngineering #Startup #DevTools #Productivity

I Built a “Typing… but Never Sends” Feature… And It Caused More Stress Than Bugs

Md Mijanur Molla — Sun, 19 Apr 2026 06:39:22 +0000

You’ve seen this.

“Typing…” appears.

You wait.

Still typing…

10 seconds…

30 seconds…

…and then?

Nothing.

👉 No message. No reply. Just silence.

So I turned this into a coding challenge.

And surprisingly… it’s not just emotional.

It’s a real system problem.

😂 The Problem

The logic seems simple:

User starts typing → show “Typing…”
User stops typing → remove it

That’s it.

But real systems don’t behave perfectly.

⚠️ What Goes Wrong?

In real-world apps:

• User stops typing but event is never sent

• Network delay causes stale state

• System keeps showing “Typing…” forever

• No timeout to clean up

And suddenly:

👉 You’re waiting for a message that will never come 😭

🧠 What I Observed

When I explored this problem:

Basic implementations rely fully on events
But events can fail or get delayed
No fallback mechanism
Stale typing status stays forever

The code works.

But the experience?

👉 Completely broken.

🔍 The Real Issue

This is not just UI.

It’s about:

• Real-time systems

• Event reliability

• State consistency

• Handling failure cases

Because:

👉 Not every “stop typing” event reaches the server

💡 What a Better System Needs

A proper typing indicator should:

Add timeout (auto-clear after a few seconds)
Refresh typing status continuously
Handle missed events
Use real-time communication (WebSockets)

This ensures:

👉 No ghost typing

👉 No fake expectations

🔥 Try My Challenge

I turned this into a fun challenge on VibeCode Arena.

👉 Try it here:
https://vibecodearena.ai/duel/8a69e643-a7cc-43c5-8829-ca9ba8914a98

Can you:

Fix “Typing forever” bug?
Handle stale state?
Build a reliable system?

🎯 Final Thought

Some bugs crash systems.

Some bugs stress users.

And this one…

👉 Does both.

So tell me 👇

Were they really typing… or just thinking? 😭

GitLab Accidentally Deleted Its Own Database… Live on Camera💀

Md Mijanur Molla — Sat, 18 Apr 2026 11:49:46 +0000

Hey guys! 👋
Today’s story is every developer’s worst nightmare… but it actually happened.

Imagine this:

👉 You run a command
👉 And suddenly… your entire production database is gone

Now imagine…

👉 Thousands of people are watching it happen LIVE 😭

💡 What Was Going On?

Back in 2017, GitLab (a platform used by developers worldwide) was facing some database issues.

Engineers were trying to fix replication problems.

Nothing unusual.

Just a normal “let’s fix production” situation.

⚠️ The Moment Everything Broke

During debugging…

An engineer ran a command to clean up some data.

But instead of deleting a small part…

👉 It deleted the primary production database

Yes. The main one.

😳 “No Problem, We Have Backups”… Right?

At this point, everyone thought:

👉 “Relax… just restore backup”

But here’s the twist:

Backups were outdated ❌
Some were corrupted ❌
Recovery was not straightforward ❌

👉 Basically… the backup plan also needed a backup

🌐 And Yes… It Was LIVE

Now this is what makes the story legendary.

Instead of hiding the issue…

👉 GitLab started a live stream

They:

Showed the real problem
Tried to fix it in real-time
Explained every step

👉 The entire internet watched engineers panic-debug 😅

🔄 The Recovery Struggle

Engineers tried everything:

Restoring partial backups
Rebuilding database state
Recovering lost data manually

It took hours of effort…

Finally:

👉 Most of the data was recovered

But the damage?

👉 Already done.

🧠 What Actually Went Wrong?

A combination of issues:

Running risky commands directly in production
Lack of proper safeguards
Weak backup verification

👉 One small mistake + poor preparation = big outage

🎯 The Real Lesson

This story is funny… but also painful.

As a developer, remember:

Never trust backups blindly
Always test recovery process
Limit direct access to production
Add confirmations for dangerous actions

🚀 Final Thought

In coding, everyone says:

👉 “It won’t happen to me”

But reality says:

👉 “Just wait…” 😄

Even top companies like **GitLab can fail.

The difference is:

👉 How you handle it when things go wrong

💬 Let’s Talk

Be honest 😄

Have you ever:

Run a command you instantly regretted?
Broken something important by mistake?

Drop your story below 👇
Let’s share some real dev pain!

TechNews #DeveloperLife #GitLab #ProductionBug #CodingMistakes #DevHumor

# I Created a “Last Seen” Challenge… And Users Stayed Online Forever 👀

Md Mijanur Molla — Fri, 17 Apr 2026 05:05:09 +0000

You’ve seen this before.

Someone is “Online”…

You send a message…

No reply.

Still “Online”…

Minutes pass… nothing.

👉 Something feels off.

This is a real-world bug.

So I created a challenge on VibeCode Arena to test how systems handle online status.

And the results were interesting.

🚨 The Problem

At first glance, the logic looks simple:

User opens app → set Online
User leaves → set Offline
Show last seen time

Everything seems correct.

But real-world systems are not that predictable.

⚠️ What Can Go Wrong?

In real applications:

• User closes app suddenly (no logout event)

• Network disconnect happens silently

• “Offline” event is never sent

• System still thinks user is online

And suddenly:

👉 User appears online forever

👉 Last seen becomes incorrect

👉 System shows misleading information

🧠 What I Observed

When AI models tried this challenge:

Some handled basic online/offline logic
Many ignored sudden disconnects
Some didn’t handle timeouts
Very few handled real-time reliability

The code works.

But the system lies.

🔍 The Real Issue

This is not just about status.

It’s about presence tracking.

Because:

👉 Events can be missed

👉 Connections can drop

👉 State can become stale

And systems must recover from that.

💡 What a Better System Needs

A proper presence system should:

Use heartbeat (ping every few seconds)
Add timeout for inactivity
Handle sudden disconnects
Use WebSockets for real-time updates
Continuously refresh user state

This ensures:

👉 Accurate online status

👉 Correct last seen

👉 Reliable user experience

🔥 Try My Challenge

I created this challenge to test real-time system thinking.

👉 Try it here:
https://vibecodearena.ai/duel/54ea165c-eb09-438b-941e-7315e8e224ac

Can you:

Fix incorrect online status?
Handle disconnects properly?
Build a reliable presence system?

🎯 Final Thought

Online status is not about showing activity.

It’s about showing accurate activity.

Because even a small delay…

👉 Can make the system look wrong.

Try it and tell me 👇

Did AI handle presence correctly… or keep users online forever?

How Passwords Are Stored Securely (Hashing, Salting, Bcrypt)

Md Mijanur Molla — Thu, 16 Apr 2026 12:13:08 +0000

When you create an account on any website…

You type your password and click Sign Up.

But here’s the question:

👉 Where does your password actually go?
👉 Is it stored as plain text?

If yes… that’s a disaster.

Let’s understand how real systems store passwords securely 👇

⚠️ First: What NOT to Do

The worst way to store passwords:

Password: mypassword123

If a database gets leaked:

👉 All user accounts are instantly compromised

This is called plain text storage
And no serious company does this.

🔒 Step 1: Hashing (One-Way Conversion)

Instead of storing the real password…

Systems store a hashed version.

Example:

mypassword123 → 482c811da5d5b4bc6d497ffa98491e38

👉 This is called hashing

Important:

It’s one-way
You cannot convert it back to original password

So even if database leaks:

👉 Attackers don’t see actual passwords

🧂 Step 2: Salting (Extra Security Layer)

Problem with hashing:

If two users have same password → same hash

That’s risky.

Solution:

👉 Add a salt (random value) before hashing

Example:

Password: mypassword123
Salt: XyZ@91

Final: mypassword123 + XyZ@91 → Hash

Now:

Same password ≠ same hash
Makes attacks much harder

⚡ Step 3: Bcrypt (Smart Hashing)

Basic hashing is not enough today.

Hackers use:

GPU attacks
Rainbow tables

So we use Bcrypt.

👉 Bcrypt is a hashing algorithm designed for passwords

It:

Automatically adds salt
Is intentionally slow
Makes brute-force attacks difficult

Example:

$2b$10$EixZaYVK1fsbw1ZfbX3OXePaWxn96p36n3c1t9v9Z8u1l9ZQFQO7e

🔄 How Login Actually Works

When you login:

You enter password
System hashes it again
Compares with stored hash

If match:

👉 Access granted

No password is ever “decrypted”

🧠 Simple Flow

👉 User Password → Add Salt → Hash (Bcrypt) → Store

That’s it.

⚠️ Common Mistakes Developers Make

Storing plain text passwords ❌
Using fast hashing (like MD5, SHA1) ❌
Not using salt ❌

👉 These make systems vulnerable

🎯 Best Practices

Always use Bcrypt (or Argon2)
Never store raw passwords
Use strong password policies
Add rate limiting for login attempts

🚀 Final Thought

Users trust your system with their data.

If passwords are not stored securely:

👉 You are risking their identity

As a developer:

Security is not optional
👉 It’s your responsibility

Now when you click “Sign Up” anywhere…

You know exactly what’s happening behind the scenes 💙

How AI Actually Writes Code (Simple Explanation for Developers)

Md Mijanur Molla — Thu, 16 Apr 2026 05:58:29 +0000

AI writing code feels like magic.

You type a prompt…
And suddenly, you get working code.

But what’s really happening behind the scenes?

Let’s break it down in simple terms 👇

💡 First Truth: AI Does NOT “Understand” Code

This might surprise you.

AI does not:

Think like a developer
Understand logic like humans
Know your exact intention

👉 It only predicts the next best word/token

Just like:
When you type on your phone → it suggests the next word

AI does the same… but at a much bigger scale.

🧠 How AI Was Trained

AI models are trained on:

Millions of code examples
GitHub repositories
Documentation
Stack Overflow discussions

From this data, it learns patterns like:

How functions are written
Common coding structures
Error patterns and fixes

👉 It becomes very good at “pattern recognition”

⚙️ What Happens When You Ask for Code

Let’s say you type:

“Create a login API in Node.js”

Here’s what AI does:

Breaks your prompt into tokens
Matches patterns from training
Predicts the most likely next tokens
Generates code step-by-step

👉 It’s basically “auto-complete on steroids”

🔍 Why AI Sometimes Gives Wrong Code

Because:

It doesn’t test the code
It doesn’t know your full project
It guesses based on probability

So sometimes:

Logic is wrong
Edge cases are missing
Code looks correct but fails

👉 That’s why blind trust = danger

⚡ Why AI Still Feels So Powerful

Even though it doesn’t “understand”…

It has seen:

Thousands of similar problems
Different coding styles
Multiple solutions

So it can:

Generate code fast
Suggest better approaches
Help debug issues

👉 It’s like learning from millions of developers at once

🧠 The Right Way to Use AI

Don’t use AI like this:

❌ Copy → Paste → Done

Use it like this:

Ask “why this code works”
Break down the logic
Modify and test
Learn from outputs

👉 Treat AI as a mentor, not a shortcut

🎯 Simple Analogy

Think of AI like:

A very smart student
Who has read everything…
But doesn’t truly understand anything deeply

👉 It can answer fast
But you still need judgment

🚀 Final Thought

AI is not magic.

It’s prediction + data + patterns.

If you understand this…

👉 You’ll stop fearing AI
👉 And start using it smartly

And that’s what makes a real developer 💙

I Created a URL Shortener Challenge… And AI Generated Duplicate Links 🔗

Md Mijanur Molla — Wed, 15 Apr 2026 05:31:06 +0000

URL shorteners look simple.

Take a long URL → generate a short code → redirect.

That’s it.

But what if two different links get the same short URL?

So I created a challenge on VibeCode Arena to test this.

And the results were surprising.

🚨 The Problem

At first glance, everything works:

Generate a random short string
Map it to the original URL
Return the short link

Simple and clean.

But there’s a hidden issue.

⚠️ What Can Go Wrong?

In real-world systems:

• Random strings can collide

• Two users may get the same short URL

• One mapping can overwrite another

• Data gets lost or mixed

And suddenly:

👉 A short link redirects to the wrong website

👉 User trust is broken

👉 System becomes unreliable

🧠 Why This Happens

The problem is randomness without guarantees.

Just generating a random string does NOT ensure uniqueness.

And without proper checks:

👉 Collisions are inevitable

🤯 What I Observed

When AI models tried this challenge:

Some generated random short codes
Many ignored collision handling
Some didn’t check existing mappings
Very few ensured uniqueness properly

The code works.

But the system is not reliable.

🔍 The Real Issue

This is not just about shortening URLs.

It’s about:

• Uniqueness

• Data integrity

• Scalability

• Reliability

Because:

👉 One collision can break multiple links

💡 What a Better System Needs

A proper URL shortener should:

Check for existing short codes
Handle collisions safely
Use hashing or encoding strategies
Store mappings in a reliable database
Scale for millions of URLs

This ensures:

👉 Every short link is unique

👉 No data is overwritten

🔥 Try My Challenge

I created this challenge to test real-world system thinking.

👉 Try it here:
https://vibecodearena.ai/duel/d3e31c10-30b4-4d61-895f-d2751e71eaaf

Can you:

Prevent duplicate short URLs?
Handle collisions properly?
Design a scalable system?

🎯 Final Thought

URL shorteners don’t fail because of code.

They fail because of edge cases and scale.

And that’s where real engineering begins.

Try it and tell me 👇

Did AI handle uniqueness properly… or create duplicate links?

# 🚀 5 Unique Project Ideas That 99% Developers Don’t Build

Md Mijanur Molla — Tue, 14 Apr 2026 10:36:37 +0000

Let’s be honest…

Everyone is building:

Todo apps ❌
Chat apps ❌
E-commerce ❌

If you want to stand out…

👉 You need something different.

Here are 5 unique, rare project ideas 👇

🧠 1. “AI Code Reviewer with Explanation”

Build a tool where:

User uploads code (GitHub / file)
AI reviews code
Gives suggestions
Explains WHY it’s wrong (simple English)

👉 Twist:
Not just “fix code” → but “teach developer”

👉 Why it’s unique:
Most tools fix… very few teach

🎯 2. “Smart Interview Simulator (AI + Voice)”

Features:

AI asks interview questions
User answers by voice
AI analyzes confidence + answers
Gives feedback

👉 Tech:
Speech-to-text + AI API

👉 Why it’s unique:
Real interview practice system

📊 3. “Real-Time Developer Productivity Tracker”

Tracks:

Coding time
Git commits
Focus time (idle detection)
Generates weekly report

👉 Bonus:
AI gives suggestions like:
“Your productivity is low in evenings”

👉 Why unique:
Personal analytics for devs

🌐 4. “Auto Portfolio Generator from GitHub”

User connects GitHub →

Auto fetch projects
Generate portfolio website
AI writes project descriptions
One-click deploy

👉 Why unique:
Solves real problem for devs

🔍 5. “Bug Reproduction AI Assistant”

User gives:

Bug description

System:

Tries to reproduce bug
Suggests possible causes
Gives debugging steps

👉 Why unique:
Debugging-focused AI (very rare)

🔥 Final Truth

If your project is:

❌ Common → ignored
✅ Unique → remembered

Don’t try to build what everyone builds.

👉 Build what makes people say:
“Bro this is different…”

That’s how you win 💙

🎙️ Top 10 AI Meeting Recorder & Note-Taker Tools (Developers Must Know)

Md Mijanur Molla — Tue, 14 Apr 2026 07:07:30 +0000

Let’s be real…

Meetings waste a lot of time 😅
And writing notes during meetings? Even worse.

That’s why AI meeting tools are becoming super popular.

They can:

Record meetings automatically
Convert speech → text
Generate summaries
Extract action items

👉 Basically, they save your time + brain power

Here are Top 10 AI Meeting Recorder / Note Tools you should know 👇

🔥 1. Otter.ai (Most Popular)

Real-time transcription
Auto summaries + action points
Works with Zoom, Meet, Teams

👉 Perfect for beginners & teams

⚡ 2. Fireflies.ai

Records + transcribes meetings
Smart search inside conversations
CRM & Slack integration

👉 Great for startups & sales teams ([Tactiq][1])

🧠 3. Notta AI

Multi-language transcription
Converts meetings → notes + tasks
Clean UI and easy export

👉 Good for students & devs ([Notta][2])

🚀 4. tl;dv

Works with Zoom & Google Meet
Highlights important moments
Free unlimited recordings

👉 Best free tool option ([tl;dv][3])

🎯 5. Fathom

Auto recording + summaries
No complicated setup
Generates action items

👉 Simple and fast tool

💡 6. Krisp AI

Removes background noise
Also provides meeting notes
Works in noisy environments

👉 Best for remote workers ([TicNote Cloud][4])

🧩 7. Tactiq

Chrome extension
Live captions + summaries
Integrates with Google Docs & Slack

👉 Lightweight & easy to use

🧠 8. Read.ai

AI meeting insights + reports
Tracks engagement & sentiment
Works across platforms

👉 Good for analytics-driven teams ([Read.ai][5])

🖥️ 9. Granola

Desktop-based (no meeting bot)
Records system audio
Enhances your notes with AI

👉 Best for privacy-focused users ([Read.ai][6])

🎨 10. Meeting.ai

Creates visual meeting notes
Turns discussion into diagrams
Easy to remember key ideas

👉 Unique visual experience ([Google Play][7])

🧠 How to Choose the Right Tool

Don’t just pick randomly. Think like a developer:

Want free tool → tl;dv
Want accuracy + collaboration → Otter.ai
Want privacy (no bots) → Granola / Meetily
Want CRM integration → Fireflies
Want visual notes → Meeting.ai

⚠️ Reality Check

AI tools are powerful…

But:

They are not 100% accurate
They can miss context
Privacy can be a concern

👉 Always review important meeting notes

🚀 Final Thought

As a developer, your time is your biggest asset.

If you are still:

Writing notes manually ❌
Forgetting meeting points ❌

Then you are already behind.

Start using AI tools.

Work smarter, not harder 💙

# 🤖 AI is Not Replacing Developers (But It’s Changing Everything)

Md Mijanur Molla — Mon, 13 Apr 2026 05:25:50 +0000

Everywhere I look, people are saying:

👉 “AI will replace developers”
👉 “Coding jobs will disappear”
👉 “No need to learn programming anymore”

Honestly… I was scared too.

But after exploring tools like ChatGPT, GitHub Copilot, and other AI tools, I realized something important:

👉 AI is not replacing developers
👉 It’s upgrading developers

💡 What AI Actually Does

AI can:

Write code snippets
Fix small bugs
Suggest improvements
Generate ideas

Sounds powerful, right?

But here’s the truth…

AI does not understand your full project.
AI does not know your business logic.
AI does not think like a real engineer.

It just predicts.

🧠 What Developers Still Do

As a developer, your job is not just writing code.

You:

Solve problems
Design systems
Make decisions
Understand users

And these things… AI cannot replace.

At least not anytime soon.

⚡ My Experience Using AI

When I started using AI tools:

At first:

I copied code blindly
I didn’t understand much

But later I changed my approach:

Now I:

Ask better questions
Understand the output
Modify the code myself

👉 That’s when AI became powerful

🚧 Biggest Mistake Beginners Make

Many beginners think:

“I don’t need to learn coding, AI will do it.”

This is dangerous.

Because:

If you don’t understand code, you can’t fix errors
If AI gives wrong output, you’ll be stuck
You become dependent instead of skilled

🔥 How to Use AI Smartly

Here’s what actually works:

Use AI as a helper, not a replacement
Always try to understand the code
Break problems into small parts
Practice without AI sometimes

👉 Balance is the key

🎯 The Future of Developers

The future is not:

❌ Developers vs AI
✅ Developers + AI

Developers who use AI smartly will:

Work faster
Build better projects
Stay ahead in the job market

🚀 Final Thought

AI is a tool.

Just like:

Calculator didn’t replace math
Google didn’t replace knowledge

AI will not replace developers.

But developers who don’t use AI…

👉 might get replaced by those who do

If you’re learning coding right now, don’t be scared.

Learn it.
Use AI.
Grow with it.

That’s the real game 💙

Forem: Md Mijanur Molla

What Really Happens When You Call an API

💡 Step 1: You Trigger the Request

🌐 Step 2: DNS Lookup (Finding the Server)

📡 Step 3: Request Travels Over the Internet

🔐 Step 4: Secure Connection (HTTPS)

⚙️ Step 5: Server Receives the Request

🧠 Step 6: Backend Processes It

🗄️ Step 7: Database Interaction

📦 Step 8: Response is Created

🚀 Step 9: Response Travels Back

💻 Step 10: Your App Uses the Data

🔄 Simple Flow

⚠️ Why Things Go Wrong Sometimes

🎯 Real Developer Insight

🚀 Final Thought

I Built an “Online but Not Replying” System… And It Created Trust Issues 😭

😂 The Problem

⚠️ What Goes Wrong?

🧠 What I Observed

🔍 The Real Issue

💡 What a Better System Needs

🔥 Try My Challenge

🎯 Final Thought

I Built a Complete Developer Hub — Introducing TechForDev

Introducing TechForDev

Core Features

1. Live Tech News (Auto-Updating)

2. AI Tools Directory

3. Developer Roadmaps

4. Job Opportunities Section

️ 5. Free APIs Collection

6. Salary Insights

⚔️ 7. Coding Challenges

8. Tech Comparison Tool

️ 9. Podcasts & Learning Resources

⚡ 10. Built-in Developer Tools

Why I Built This

What’s Next?

Your Feedback Matters

Tags

WebDevelopment #Developers #BuildInPublic #Tech #AI #Coding #SoftwareEngineering #Startup #DevTools #Productivity

I Built a “Typing… but Never Sends” Feature… And It Caused More Stress Than Bugs

😂 The Problem

⚠️ What Goes Wrong?

🧠 What I Observed

🔍 The Real Issue

💡 What a Better System Needs

🔥 Try My Challenge

🎯 Final Thought

GitLab Accidentally Deleted Its Own Database… Live on Camera💀

💡 What Was Going On?

⚠️ The Moment Everything Broke

😳 “No Problem, We Have Backups”… Right?

🌐 And Yes… It Was LIVE

🔄 The Recovery Struggle

🧠 What Actually Went Wrong?

🎯 The Real Lesson

🚀 Final Thought

💬 Let’s Talk

TechNews #DeveloperLife #GitLab #ProductionBug #CodingMistakes #DevHumor

# I Created a “Last Seen” Challenge… And Users Stayed Online Forever 👀

🚨 The Problem

⚠️ What Can Go Wrong?

🧠 What I Observed

🔍 The Real Issue

💡 What a Better System Needs

🔥 Try My Challenge

🎯 Final Thought

How Passwords Are Stored Securely (Hashing, Salting, Bcrypt)

⚠️ First: What NOT to Do

🔒 Step 1: Hashing (One-Way Conversion)

🧂 Step 2: Salting (Extra Security Layer)

⚡ Step 3: Bcrypt (Smart Hashing)

🔄 How Login Actually Works

🧠 Simple Flow

⚠️ Common Mistakes Developers Make

🎯 Best Practices

🚀 Final Thought

How AI Actually Writes Code (Simple Explanation for Developers)