The world of software engineering is being shaken up, and if you’re not aware of it yet, well, you should be. We’re talking about AI and Machine Learning taking the center stage, and traditional software stacks are already looking a bit outdated. So, let’s take a moment and explore what it means for us, particularly the younger folks getting into this game.

Remembering the Old Days of Tech Change

Now, I’ve been around the block since ’69, so I’ve seen a fair share of tech curves. Think back to when COBOL, Fortran, or C compilers came on the scene. Some old-school developers thought it was a joke. “Real programmers write assembler code”, they’d scoff. But guess what? High-level languages made coding at least three times quicker, and the folks who adapted? They survived. The others? Not so much.

Let’s not forget the era when databases were the new kid on the block. The naysayers preferred meticulously crafted ISAM files, but suddenly, everyone had to get onboard. The industry changed completely, and if you simply refused to learn, well, you were out of luck. These are well-documented changes, too, and anyone can read up on them if they wish.

The Big Wave: Large Language Models

Now, with all that history, we find ourselves facing another tech tsunami: Large Language Models, or LLMs. They’re not just fancy tools; they’re fundamentally altering how we think about and build software. They can generate code, explain APIs, propose architectural designs, and pinpoint security issues—all tasks that previously took even the most seasoned devs hours or days. Sure, they’re not perfect, but they’re impressively useful.

It’s not just about writing code, either. They’re shaking up the entire software lifecycle. They can take a vague business request, turn it into a coherent user story, refine it into a golden specification, and help us with design patterns. They work faster than you can type out boilerplate code and spot issues that experienced developers might miss during code reviews.

Why You Should Care

You might think you’ve got the skills to weather this storm. You survived this and that wave before. But here’s the rub: every wave is stronger than the last, fundamentally reshaping how we view software development. The productivity boosts and competitive pressures stemming from LLMs are catching the eyes of managers, CTOs, and investors. They see the potential to produce top-notch software faster and cheaper, while bypassing the “diva developers.”

Let’s be blunt: technological disdain will not halt a tsunami. History proves this. Technological arrogance only leaves you in the cold. From assembler to high-level languages to GUIs, each wave reshaped our industry. The shift from mainframes to cloud computing is a prime example of how new tech has altered our paths. Some smart folks have even written about it!

It’s Time to Get Ready

This is the moment for action. Acknowledge that LLMs aren’t just a fad. Their flaws don’t eclipse their raw utility. Use them to enhance what you do. Dive into them for everything—design, testing, code generation, refactoring. Adapt or prepare for a long wait on the sidelines while others seize the day.

I’ve seen it too often, and I’m saying it again: the wave is on its way. You can sense it already. The shoreline is receding. So, ride it or be left behind, scavenging for whatever’s left. It’s your call.

Wrapping It Up

We’re on the brink of a new age in software engineering, one where AI and Machine Learning aren’t just tools but are pivotal to innovation. If you want to stay relevant, you need to embrace these changes and get to grips with LLMs. The clock is ticking!

The author does not own or have any interest in the securities discussed in the article.