Coding Is Changing. Here's How I Stay AHEAD

The AI revolution isn't replacing engineers (IMHO) - it's changing how they work and which skills matter most.

I mean, look at the sponsor of this week, a "vibe coding" platform that creates your idea in no time.
But, does it actually matter for developers / devops and other tech engineers?

Well.. Yes and no, stay with me.

While LLMs leveraged by platforms like Lovable can now generate landing pages in 2 hours that once took days, the developers who will thrive aren't those fighting against AI, but those who master the deep skills that are beyond just producing lines of code.

Companies are scaling back hiring as AI handles more routine coding tasks, but I don't think this trend will hold.

Despite fear and anxiety, driven mainly by those who have something to gain (media channels selling ads, or AI CEOs), an opposite truth emerges:

AI isn't eliminating programmers - it's empowering them to replace everyone else.
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Existing systems today are already trivially easy it is to exploit (example coming up) - from accessing other users' profiles by manipulating IDs to creating free guest passes on your local gym, by simply by intercepting and modifying responses.

Heck, I found a payment bypass on my home country's border control during Covid.
I reported it. It was completely ignored.

With AI generated code, which is trained on insecure code to begin with, things get worse.
LLMs are not cheap when working with large contexts, and while there's an ever-going race to infinity on the size of context they can digest, they're kind of fighting with themselves:

AI is growing the context by generating more code, and trying to consume it all to build more features.

This is kind of messed up if you think about it.

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So, what can we do?

The solution (again, IMO) isn't to abandon AI tools but to develop complementary skills most resistant to automation, and the ones that require large contexts.

"Big-picture stuff", if you will.

Three critical areas stand out: hacking/security knowledge, defensive coding practices, and advanced debugging.

These capabilities represent the human oversight that keeps AI-accelerated development from becoming a nightmare. (Educated guess: IT WILL).

For security skills, resources like OWASP's Top 10 vulnerabilities list, Damn Vulnerable Web App, and platforms like HackTheBox and Hacker1 provide structured learning paths, and making some profit if you're willing to invest some (a lot) of time.

For defensive coding, tools like Git leaks and Trivy can scan for vulnerabilities, while the 12 Factor App manifesto offers guiding principles for properly constructed applications.

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Most importantly, debugging remains the crucial skill that separates professionals from AI-dependents.

If you've vibe-coded recently, at some point, you've encountered a bug. You probably asked your favorite LLM to try and fix it, only to end up arguing with, typing "still not working" over and over.

It's time to admit it: problem solving isn't going away anytime soon.

When faced with complex bugs, professionals don't just layer more AI onto problems caused by AI - they methodically use debuggers, set breakpoints, and follow processes to root out issues that even the most advanced AI struggles to identify.

Those who thrive in this new era won't be the ones who know how to prompt an AI to generate a landing page.

They'll be the ones who understand how systems can break, how to secure them properly, and how to fix them when they inevitably fail.

These are "DevSecOps" professionals - and don't kill me for the buzzword, it addresses engineers who can write bust most importantly READ code, they know appsec, and potentially, some ops (devops) processes to complete their skillset.
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The bottom line?

Don't fight AI - prepare for your elevated role within it.

The age of AI doesn't spell the end of developers - it elevates those who can oversee, secure, and maintain what AI helps create.

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Thank you for reading.
Feel free to reply directly with any question or feedback.
Have a great weekend!