Tag Archives: AI

Chrome, JavaScript, webdev

Building a Real-Time Pull-Up Tracker: How I Taught The Browser to Count Our Pain

It started as a simple idea my son brought up: Can we make a web app that counts our pull-ups during our pull-up games?

Turns out, teaching a machine to recognize human suffering is both hilarious and complicated.
What began as a “let’s make a quick pull-ups app” spiraled into an intense journey through computer vision, browser quirks, and a few accidental infinite loops that made our laptop sound like a jet engine.

The “Simple” Goal

I wanted to automatically count pull-ups using a web camera.

Easy, right?

Just detect a human, see when they go up and down, and count.

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Business, JavaScript, webdev

Craft Exceptional Web Experiences as a Full-Stack Engineer

At EspressoLabs.com, we’re on a mission to redefine the future of IT/Security management through exceptional user experiences and cutting-edge technology.
We believe that enterprise software should not only be powerful and scalable but also intuitive, elegant, and a joy to use.

We’re building a platform that merges AI-intelligence with seamless design—and we’re looking for a Full-Stack Developer who shares our passion for creating meaningful, impactful technology.

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JavaScript, webdev

The Future of Coding: LLMs as Collaborators

The rise of large language models (LLMs) has been one of the most transformative developments in software engineering in decades. Tools like GPT4.1, Gemini 2.5 Pro, Claude Opus 4, and various AI-powered code editors such as Cursor (or CoPilot) promise to change the way we build software.

But as these tools evolve and mature, the real question isn’t if we should use LLMs—it’s how.

There’s an emerging split in philosophy between two approaches: full automation through AI agents and IDE integrations, or human-led development using LLMs as intelligent partners.

Based on real-world experiences and a critical review of LLM-based coding tools, the most effective path today is clear:

LLMs are best used as powerful amplifiers of developer productivity—not as autonomous builders.

Let’s break down why.

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cloud, webdev

How to Use ngrok and LocalTunnel: Expose Your Local APIs to the World

Intro

As developers, we often face the challenge of testing our local applications with external services, webhooks, or mobile devices. Whether you’re developing APIs that need to communicate with AWS/GCP/Azure services, testing webhook integrations, or simply want to demo your work from different devices, exposing your localhost to the internet becomes essential.

This guide will walk you through two popular solutions: ngrok and LocalTunnel, showing you how to securely expose your local development server to the world.

What Are Tunneling Services?

Tunneling services create a secure tunnel from a public endpoint to your local machine, allowing external services to reach your development server without complex network configuration or deployment.

Common Use Cases

  • Testing webhooks from third-party services (Stripe, GitHub, etc.) — You can connect your local code directly and debug it more efficiently.
  • Sharing your work-in-progress with clients or team members — Instead of pushing it to some remote server. Useful in all the cases, where you are still ‘not ready’.
  • Testing mobile applications that need to connect to your local API — A must have in almost all cases.
  • Integrating with AWS services that require publicly accessible endpoints
  • Cross-device testing and debugging
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webdev

Mastering Clean Code: 15 Key Lessons for Software Developers

Years ago (when Java was ‘new’), I got a recommendation from a good friend to check out “Ah, Clean Code by Robert C. Martin”. He told me, “It’s not just a book; it’s a must-read to anyone who wishes to be a professional software developer.”

He was right. This is still one of the top five books that I recommend developers read. It focuses on some simple but important concepts that will make your Code better, simpler, and easier to debug.

More than aesthetics, clean Code is about clarity, maintainability, and efficiency. Investing in writing clean Code might seem time-consuming, but it pays off exponentially in debugging, collaboration, and scaling efforts.

Think of messy Code as a tangled web: complex to navigate and easy to get stuck in. Clean Code teaches you to weave a well-structured tapestry instead—clear, elegant, and easy to extend.

Here are 15 powerful lessons every developer should carry from this book, with practical examples:

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Business

Leveraging AI for Efficient Code Reviews

In today’s fast-paced development environment, leveraging AI tools for code reviews can significantly enhance productivity and code quality. As developers, we often work in isolation or wait hours (sometimes days) for our colleagues to review our pull requests. Large Language Models (LLMs) like GPT-4, Claude, and others can provide immediate feedback, spot potential issues, and suggest improvements within your favorite IDE.

This blog post explores how to craft effective prompts for LLMs when reviewing your code in VSCode, with specific examples for backend Node.js/Express developers and React frontend developers.

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Business

Securing Your (NodeJS) Backend: A Comprehensive Guide to Preventing Common Attacks

Web security is a critical concern for any backend developer. If you’re building applications using Node.js and Express, it’s essential to safeguard your backend against common security threats such as SQL injections, cross-site scripting (XSS), cross-site request forgery (CSRF), and other vulnerabilities. This comprehensive guide explores these attacks in depth and demonstrates best practices to prevent them with practical coding examples.

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JavaScript, webdev

Why/How Senior Engineers Embrace AI Tools in Development?

How can you do better (or succeed more) with AI coding tools?

Senior engineers who use AI tools (co-pilot, claude.ai, cursor, etc.) are like master chefs who know when to use the microwave and when to actually cook with fire.

Here are some of the bold aspects I’ve noticed in the past year:

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Business

The Art of AI Conversation: 6 Essential Tips for Chat LLM Success

When working with Large Language Models (LLMs) in a chat interface, understanding how to effectively communicate and leverage their capabilities can significantly improve your results. This involves crafting clear and specific prompts, providing necessary context, and breaking down complex tasks into manageable steps. It’s important to recognize that while LLMs possess vast knowledge, they require precise guidance to deliver optimal outputs. Users should be prepared to iterate on their queries, refine their instructions, and engage in a collaborative back-and-forth to achieve desired outcomes. Additionally, being aware of the model’s limitations, such as potential biases or outdated information, allows users to critically evaluate responses and seek clarification when needed.

Btw, if you wish to save and improve your prompts over time – you can use your VScode editor or a platform like latitude.

Here are six essential tips to enhance your experience:

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JavaScript, webdev

The Power of Many: Why You Should Consider Using Multiple Large Language Models

Large Language Models (LLMs) have taken the world by storm. These AI systems can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way. But with so many LLMs available, each with its own strengths and weaknesses, how do you choose the right one for the task? 

The answer might surprise you: it’s about more than picking just one. Here’s why using multiple LLMs can be a powerful approach.

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