Welcome to BEON.tech's blog

Software organizations are under constant pressure to ship faster, innovate continuously, and keep top talent engaged. Yet, despite the billions poured into new tools and methodologies, productivity gains have plateaued. Developers spend more time battling slow build pipelines, redundant tasks, and siloed communication than writing the code that drives business value. The result? Burnout, rising...

It’s no secret that AI tools are reshaping how developers work. From automating boilerplate code to boosting daily productivity, artificial intelligence has evolved from a sidekick to a co-pilot — and in many cases, the pilot itself. The adoption of these tools is rapidly becoming the norm, with usage rates ranging from 70% to 82%...

Embarking on a new product is a defining moment for any company. You’re about to build something big, but will the underlying tech stack you choose today sustain your vision years from now? Picking a tech stack isn’t just a developer’s decision; it’s a strategic business choice that shapes your product’s speed, scalability, and maintainability. ...

Your app was running just fine. Until one day, users started showing up, and with them, the bottlenecks. The endpoint that worked perfectly now takes 10 seconds. And there you are, digging through logs, wondering where everything went wrong. The good news? You’re not alone. Optimizing software isn’t magic, but it’s also not luck. It’s...

In today’s microservices architecture, you might have several services in one repository, you even may have a monorepo with all your applications in a single place! But what if only a single service changed? What if a subset of them changed? In this tutorial, we’ll set up a GitHub Action that: Let’s dive in step-by-step! ...

The rapid rise of AI applications — from customer service chatbots to sophisticated generative design tools — has placed data quality at the heart of AI development. While high-quality training data is essential for building reliable, high-performing models, not all data is created equal. Broadly, AI training datasets fall into two main categories: Each type...

Code-generating large language models (LLMs) are transforming software development. By automating repetitive coding tasks, assisting with debugging, and even generating functional code from simple prompts, these models allow development teams to work faster, more efficiently, and with greater focus on complex challenges. As businesses increasingly adopt AI-powered tools to streamline operations and reduce development cycles,...

Frontend development has come a long way since the days of static HTML pages and simple styling. Today’s web interfaces are fast, interactive, and dynamic—closer to full-blown applications than websites. And over the past five years, we’ve seen another major shift in the evolution of frontend development: from monolithic frontend codebases to modular architectures, performance-optimized...

Frontend development has evolved into a high-stakes balancing act—where engineers juggle design fidelity, performance, accessibility, and fast-changing frameworks. At the same time, AI is no longer just enhancing developer productivity. It’s actively reshaping how interfaces are designed, built, and maintained. In practice, AI in frontend development means tools are emerging that go beyond simple code...