The Rapidly Changing World of Tech

In the world of tech, everything is changing rapidly. Every single day, a new technology is developed or introduced. No matter what you do, you’re always trying to keep up.

We’re constantly trying new things, exploring, and finding use cases for the latest tech. Sometimes, we even contribute to the technologies we love.

For instance, if you’re a web developer, you might be working with JavaScript and contributing to its community. Or, if you’re an Android developer, you could be having fun with Flutter, Dart, or even Kotlin.

It’s all good! The tools you use daily are the ones you give back to, whether by contributing to their development or supporting them through sponsorships. And that’s great—it’s entirely up to you.

The Innovation Gap

However, in recent years, I’ve noticed something: an innovation gap.

What is this innovation gap? It’s a question that needs answering. Here’s how I see it: the innovation gap occurs when there isn’t enough substantial content or features to justify every single release.

In other words, the frequency of releases creates an illusion of constant innovation, but the changes themselves may not be groundbreaking.

The Past vs. Now

Think about the past. Each new release of a technology was massive—new features, fresh ideas, improved UI—something that made users excited to upgrade. Every release felt significant and worth learning.

This applied to everything, from mobile device technology to software tools. For example:

• Visual Studio Code: When it was introduced, it changed how we viewed code editors.
• Neovim’s Lua Support: A massive improvement that reshaped how developers interacted with Neovim.

Now, let’s talk about Machine Learning.

If you’ve been following the news, OpenAI has released several models alongside new tiers and services. But the newer releases don’t feel as groundbreaking as earlier ones.

For example:

• The leap from GPT-2 to GPT-3 (and GPT-3.5) was massive. These models transformed how we interacted with AI, answered questions, generated code, and more.
• On the other hand, GPT-4 and GPT-4-turbo are good, but they don’t feel like they’ve made a similarly huge leap forward.

It feels like smaller changes are being packaged as something big, which makes switching to the newer versions less exciting.

React’s Evolution: A Case Study

Take React as another example. React revolutionized how we build UIs and pushed JavaScript to the server. With each update, React made things better and better.

However, its approach to innovation has shifted. Smaller releases accumulate over time and eventually combine into a big release.

For instance:

• The move from class components to functional components with hooks was a significant paradigm shift.
• React 19 introduces a new compiler, breaking many older features, which feels massive only because it bundles several smaller changes together.

A Better Approach: Svelte and Next.js

Now, look at how frameworks like Svelte and Next.js handle releases.

• Svelte 5 was released with huge changes, making it exciting for users.
• Similarly, Next.js 15 introduced a bundle of improvements, which felt like a fresh start.

I’ve never used Next.js before, but the changes in version 15 pushed me to try it. The features in both the new and old versions complement each other, making the framework fun and exciting to use.

Final Thoughts

Are you seeing the pattern here? Smaller releases accumulate into one big release, but the hype around each small announcement feels unnecessary.

In my opinion, tech companies should avoid releasing minor updates frequently. Instead, focus on bundling them into one major release. If you’re making core structural changes, then small updates are fine. But if it’s just adding features, wait until there’s enough content to justify a big update.

This approach keeps releases exciting and users engaged. That’s why I appreciate how Svelte and Next.js handle their versioning. It makes tech more fun to explore and use.

Until then, keep coding, nerds! ❤️