DEV Community: Dev Sk

⚡ TSRX – A New Way to Write UI in TypeScript

Dev Sk — Tue, 12 May 2026 04:30:00 +0000

You can think of TSRX as a spiritual successor to JSX — the same idea of embedding UI directly inside TypeScript, but with its own flavor.

✨ What makes TSRX different:

🌀 Control flow, scoped styles, and locals are first-class syntax in the template (not squeezed through expression slots).

🧩 The language stays aware of them all the way through to the compiled output.

🌐 It’s framework-agnostic and interoperable — today it compiles to React, Preact, Ripple, Solid, and Vue, with more to come.

📦 You can import .tsrx modules from JS, TS, and TSX files — and it just works.

👉 In short: TSRX keeps the mental model of JSX but evolves it into something more powerful, flexible, and future-ready.

🔗 Learn more: tsrx.dev

🚀 New in Chrome 148: Three Features You Shouldn’t Miss

Dev Sk — Sun, 10 May 2026 04:00:00 +0000

Google Chrome continues to evolve, and version 148 introduces powerful updates for developers:

1️⃣ CSS name-only container queries – Query containers by name without needing a container-type.
2️⃣ Lazy loading for video & audio – The loading attribute now works for media elements, aligning with img and iframe.
3️⃣ Prompt API with Gemini Nano – Direct access to on-device AI for text, image, and audio inputs, with response constraints via JSON schema and regex.

These changes make front-end workflows more efficient, improve performance, and open doors for AI-powered web experiences.

🔗 Full article: developer.chrome.com/blog/new-in-chrome-148

WebDevelopment #ChromeUpdate #Frontend #CSS #LazyLoading #AI #GeminiNano #JavaScript #WebPerformance #PromptAPI

🌐 The End of the UI

Dev Sk — Wed, 29 Apr 2026 04:44:14 +0000

🌐 The End of the UI: Why Salesforce Headless 360 Changes Everything for AI Agents

For years, business software has been all about the user interface — dashboards, forms, and clicks. But Salesforce’s new Headless 360 changes the game.

Instead of relying on screens, it opens up data and workflows through APIs. This means AI agents can work directly with Salesforce — updating records, running campaigns, and handling customer journeys — without a human clicking around.

Why this matters:
AI-first operations: Agents can take care of routine tasks automatically.
Flexible integration: Salesforce connects easily with other systems, no UI redesign needed.

More human time: Teams spend less effort navigating menus and more time on strategy and relationships.
This is the start of a UI-less enterprise era. Your CRM doesn’t wait for you to log in — your AI agent already knows what to do and gets it done.

💡 The question is no longer “How do I use Salesforce?” but “How will my AI agent use it for me?"

✨ Did you know Git has a hidden gem called Git Worktree?

Dev Sk — Mon, 27 Apr 2026 05:14:26 +0000

Most of us switch branches by stashing changes, checking out, and then losing track of what we were doing. But Git Worktree makes this so much easier.

👉 With worktree, you can check out multiple branches at the same time, each in its own folder, but all connected to the same .git repo.

Why it’s useful:
Keep a long build running while you code a new feature

Review a PR branch without disturbing your main workspace

Test deployment scripts across different branches side by side

The best part? No extra setup. It’s already built into Git — yet many developers don’t even know it exists.

If you’re juggling multiple branches daily, Git Worktree can save you time and headaches.

💬 Have you tried it before? How has it changed your workflow?

Top 30 AWS Services That Are Commonly Used

Dev Sk — Wed, 07 May 2025 18:28:14 +0000

Top 30 AWS Services That Are Commonly Used
We group them by category and understand what they do.

Compute Services
1 - Amazon EC2: Virtual servers in the cloud
2 - AWS Lambda: Serverless functions for event-driven workloads
3 - Amazon ECS: Managed container orchestration
4 - Amazon EKS: Kubernetes cluster management service
5 - AWS Fargate: Serverless compute for containers

Storage Services
6 - Amazon S3: Scalable secure object storage
7 - Amazon EBS: Block storage for EC2 instances
8 - Amazon FSx: Fully managed file storage
9 - AWS Backup: Centralized backup automation
10 - Amazon Glacier: Archival cold storage for backups

Database Services
11 - Amazon RDS: Managed relational database service
12 - Amazon DynamoDB: NoSQL database with low latency
13 - Amazon Aurora: High-performance cloud-native database
14 - Amazon Redshift: Scalable data warehousing solution
15 - Amazon Elasticache: In-memory caching with Redis/Memcached
16 - Amazon DocumentDB: NoSQL document database (MongoDB-compatible)
17 - Amazon Keyspaces: Managed Cassandra database service

Networking & Security
18 - Amazon VPC: Secure cloud networking
19 - AWS CloudFront: Content Delivery Network
20 - AWS Route53: Scalable domain name system (DNS)
21 - AWS WAF: Protects web applications from attacks
22 - AWS Shield: DDoS protection for AWS workloads

AI & Machine Learning
23 - Amazon SageMaker: Build, train, and deploy ML models
24 - AWS Rekognition: Image and video analysis with AI
25 - AWS Textract: Extracts text from scanned documents
26 - Amazon Comprehend: AI-driven natural language processing

Monitoring & DevOps
27 - Amazon CloudWatch: AWS performance monitoring and alerts
28 - AWS X-Ray: Distributed tracing for applications
29 - AWS CodePipeline: CI/CD automation for deployments
30 - AWS CloudFormation - Infrastructure as Code (IaC)

Over to you: Which other AWS service will you add to the list?

technology #innovation #future #techupdate" #technews #futuretech #innovation #AI #automation #techtrends #digitaltransformation #fullstackdeveloper

reactdeveloper

9 OOP Design Patterns You Must Know

Dev Sk — Sun, 04 May 2025 11:54:44 +0000

9 OOP Design Patterns You Must Know

A-Creational Patterns

Deal with object creation mechanism to decouple the client code from concrete classes.

Factory Pattern: Centralizes object creation logic and returns different subclasses based on input

Singleton Pattern: Ensures only one instance of a class exists and provides global access to it.

Builder Pattern: Constructs complex objects step-by-step, allowing optional configuration.

B - Structural Patterns

Help compose classes and objects into larger structures.

Adapter Pattern: Allows incompatible interfaces to work together by translating one interface into another.

Decorator Pattern: Adds new behavior to objects dynamically without altering their original structure.

Proxy Pattern: Acts as a placeholder for accessing another object.

C - Behavioral Patterns

Focus on communication and interaction between objects.

Strategy Pattern: Allows selecting an algorithm or behavior from a family of interchangeable strategies at runtime.

Observer Pattern: Enables a one-to-many dependency so that when one object changes state, all its dependents are notified.

Command Pattern: An object encapsulates all information needed to perform an action or trigger an event.

Over to you: Which of these patterns have you used?

Essential Git Cheatsheet!

Dev Sk — Fri, 02 May 2025 12:10:28 +0000

Essential Git Cheatsheet!

🔧 Basic Commands

git init – Initialize a new Git repository.
git clone – Clone a remote repository.
git status – Check the status of your working directory.
git add – Stage changes for commit.
git commit -m "message" – Commit staged changes with a message.
git push – Push your local commits to the remote repository.
git pull – Fetch and merge changes from the remote repo.
git diff – Show changes in the working directory (uncommitted changes).
git diff --staged – Show changes between the staging area and last commit.

🛠️ Branching & Merging

git branch – List branches.
git branch – Create a new branch.
git checkout – Switch to another branch.
git checkout -b – Create and switch to a new branch.
git merge – Merge a branch into the current one.
git branch -d – Delete a branch after merging.
git branch -D – Forcefully delete a branch, even if it hasn’t merged.

🔄 Synchronizatio
git fetch – Download changes from remote without merging.
git rebase – Reapply commits on top of another branch to maintain linear history.
git pull --rebase – Fetch and reapply your changes on top of the latest remote changes.
git remote add – Add a new remote repository.

🎯 Advanced Git

git stash – Temporarily save changes without committing.
git stash pop – Reapply stashed changes.
git cherry-pick – Apply a specific commit to your current branch.
git log --oneline – View simplified commit history.
git reflog – Show the history of your reference changes (e.g., checkout, resets).
git log --graph --decorate --all – Show a visual commit history.

🚨 Undoing Changes

git reset – Unstage a file.
git reset --soft – Reset to a commit but keep changes in the working directory.
git reset --hard – Completely reset to a previous commit, discarding changes.
git revert – Create a new commit that undoes a specific commit.

⚙️ Collaborating with Others

git fork – Fork a repository on GitHub (via UI) to start contributing.
git pull origin – Pull changes from the original remote branch.
git push origin – Push your branch to the original repository for collaboration.

Over to you: did we miss anything?

technology #innovation #future #techupdate" #technews #futuretech #innovation #AI #automation #techtrends #digitaltransformation #fullstackdeveloper

reactdeveloper

What is an AI agent?

Dev Sk — Wed, 30 Apr 2025 11:38:58 +0000

What is an AI agent?

An AI agent is a software program that can interact with its environment, gather data, and use that data to achieve predetermined goals. AI agents can choose the best actions to perform to meet those goals.

Key characteristics of AI agents are as follows:

An agent can perform autonomous actions without constant human intervention. Also, they can have a human in the loop to maintain control.

Agents have a memory to store individual preferences and allow for personalization. It can also store knowledge. An LLM can undertake information processing and decision-making functions.

Agents must be able to perceive and process the information available from their environment.

Agents can also use tools such as accessing the internet, using code interpreters and making API calls.

Agents can also collaborate with other agents or humans.

Multiple types of AI agents are available such as learning agents, simple reflex agents, model-based reflex agents, goal-based agents, and utility-based agents.

A system with AI agents can be built with different architectural approaches.

Single Agent: Agents can serve as personal assistants.

Multi-Agent: Agents can interact with each other in collaborative or competitive ways.

Human Machine: Agents can interact with humans to execute tasks more efficiently.

Over to you: Have you used AI Agents?

technology #innovation #future #techupdate" #technews #futuretech #innovation #AI #automation #techtrends #digitaltransformation #fullstackdeveloper

reactdeveloper

What do version numbers mean?

Dev Sk — Sun, 27 Apr 2025 15:50:58 +0000

What do version numbers mean?

Semantic Versioning (SemVer) is a versioning scheme for software that aims to convey meaning about the underlying changes in a release.

SemVer uses a three-part version number: MAJOR.MINOR.PATCH.

MAJOR version: Incremented when there are incompatible API changes.

MINOR version: Incremented when functionality is added in a backward-compatible manner.

PATCH version: Incremented when backward-compatible bug fixes are made.

Example Workflow

Initial Development Phase
Start with version 0.1.0.

First Stable Release
Reach a stable release: 1.0.0.

Subsequent Changes
Patch Release: A bug fix is needed for 1.0.0. Update to 1.0.1.

Minor Release: A new, backward-compatible feature is added to 1.0.3. Update to 1.1.0.

Major Release: A significant change that is not backward-compatible is introduced in 1.2.2. Update to 2.0.0.

Special Versions and Pre-releases
Pre-release Versions: 1.0.0-alpha, 1.0.0-beta, 1.0.0-rc.1.
Build Metadata: 1.0.0+20130313144700.

What is the difference between Process and Thread

Dev Sk — Fri, 25 Apr 2025 13:23:52 +0000

What is the difference between Process and Thread

To better understand this question, let’s first take a look at what is a Program. A Program is an executable file containing a set of instructions and passively stored on disk. One program can have multiple processes. For example, the Chrome browser creates a different process for every single tab.

A Process means a program is in execution. When a program is loaded into the memory and becomes active, the program becomes a process. The process requires some essential resources such as registers, program counter, and stack.

A Thread is the smallest unit of execution within a process.

The following process explains the relationship between program, process, and thread.

The program contains a set of instructions.

The program is loaded into memory. It becomes one or more running processes.

When a process starts, it is assigned memory and resources. A process can have one or more threads. For example, in the Microsoft Word app, a thread might be responsible for spelling checking and the other thread for inserting text into the doc.

Main differences between process and thread:

Processes are usually independent, while threads exist as subsets of a process.

Each process has its own memory space. Threads that belong to the same process share the same memory.

A process is a heavyweight operation. It takes more time to create and terminate.

Context switching is more expensive between processes.

Inter-thread communication is faster for threads.

Over to you:

Some programming languages support coroutine. What is the difference between coroutine and thread?

How to list running processes in Linux?

The Data Engineering Roadmap

Dev Sk — Wed, 23 Apr 2025 12:51:37 +0000

The Data Engineering Roadmap

Here’s a roadmap that can help you get better at data engineering:

Programming Languages
Learn SQL and a few programming languages like Python, Java, and Scala.

Processing Techniques
Learn batch processing tools like Spark and Hadoop and stream processing tools like Flink and Kafka.

Databases
Focus on both relational and non-relational databases. Some examples are MySQL, Postgres, MongoDB, Cassandra, and Redis.

Messaging Platforms
Master the use of platforms like Kafka, RabbitMQ, and Pulsar.

Data Lakes and Warehouses
Learn about various data lake and warehousing solutions such as Snowflake, Hive, S3, Redshift, and Clickhouse. Also, learn about Normalization, Denormalization, and OLTP vs OLAP.

Cloud Computing Platforms
Master the use of cloud platforms like AWS, Azure, Docker, and K8S

Storage Systems
Learn about the key storage systems like S3, Azure Data Lake, and HDFS

Orchestration Tools
Learn about orchestration tools like Airflow, Jenkins, and Luigi

Automation and Deployments
Learn automation tools such as Jenkins, Github Actions, and Terraform.

Frontend and Dashboarding
Master the use of tools like Jupyter Notebooks, PowerBI, Tableau, and Plotty

Over to you: What else will you add to the Data Engineering Roadmap?

technology #innovation #future #techupdate" #technews #futuretech #innovation #AI #automation #techtrends #digitaltransformation #fullstackdeveloper

reactdeveloper

Coupling and Cohesion: The Two Principles for Effective Architecture

Dev Sk — Mon, 21 Apr 2025 11:57:59 +0000

Coupling and Cohesion: The Two Principles for Effective Architecture

Every large system that spirals out of control starts the same way: small, functional, and deceptively simple. However, as the system evolves, things spiral out of control.

A feature is added here, a helper function squeezed there, and a “temporary” dependency for some urgent task that never gets removed. Months later, debugging requires going through five layers of indirection, and touching one module can break the entire system.

Behind the scenes of that slow collapse, two invisible forces often play tug-of-war: coupling and cohesion.

Most developers first hear these terms in textbooks or blog posts, often lumped into a “good design” checklist.

High cohesion: good.

Loose coupling: also good.

But beyond the concepts, the practical meaning often gets lost. What does coupling look like? When does cohesion break down in real teams? And why do some projects feel like a breeze to change, while others offer challenges with every pull request?

Coupling and cohesion aren’t abstract guidelines. They are practical engineering realities that define how easily code could evolve, how confidently teams could deploy, and how painful it becomes to onboard a new teammate or fix a bug under pressure.

In this article, we’ll attempt to understand coupling and cohesion in more realistic terms and how they might show up in different architectural styles and patterns.

technology #innovation #future #techupdate" #technews #futuretech #innovation #AI #automation #techtrends #digitaltransformation #fullstackdeveloper