AI: The Digital Tapeworm Eating Your Growth

Sugeng enjang, you beautiful, misguided code-monkeys and digital dreamers! Grab your Kopi Tubruk, sit down, and listen to your Uncle Edan. Today, we are going to talk about the shiny, hallucinating elephant in the room. Everyone—from your CEO who can’t open a PDF to your junior developer who thinks “Git” is a social media platform—is screaming about how Artificial Intelligence is the ultimate fertilizer for human potential. They tell you it will make you faster, smarter, and more “evolved.”

But here is the “Wong Edan” truth: AI is not a fertilizer. It is a digital tapeworm. It doesn’t grow you; it eats the very mechanism through which growth occurs. It is a shortcut to a destination that only matters if you actually walked the path to get there. You think you are “supercharged,” but in reality, you are just outsourcing your brain to a statistical model that has the confidence of a cult leader and the actual understanding of a parrot on LSD.

The Great Illusion of the ‘Struggle-Free’ Success

Let’s start with the fundamental lie: that friction is the enemy. In the modern tech world, we are obsessed with “frictionless” experiences. We want zero-latency code, zero-click deployments, and now, zero-thought logic. But here is the biological reality that your favorite AI hype-man won’t tell you: Growth is a byproduct of friction.

When you spend four hours debugging a race condition in a distributed system, your brain is doing something magnificent. It is building neural pathways. It is mapping the architecture of the system into your subconscious. You are suffering, yes. You are frustrated. You might even be questioning your life choices and considering opening a goat farm in Central Java. But that struggle is exactly where the expertise is forged. When you finally find that one missing semicolon or that flawed logic gate, that “Aha!” moment isn’t just a dopamine hit; it’s the cement drying on a new layer of mastery.

Now, enter the AI. You feed the error to a Chat-based model. It spits out the fix in three seconds. You copy. You paste. It works. You feel productive. But what did you actually learn? Nothing. You didn’t trace the logic. You didn’t understand the “why.” You just skipped the gym and took a photo of someone else’s muscles. As noted in recent critiques of ChatGPT-5 and its predecessors, when generative AI shortcuts the process, it doesn’t assist—it replaces the very struggle that leads to growth. You aren’t becoming a better engineer; you are becoming a glorified librarian for a library you didn’t build and don’t understand.

Refactoring the Past vs. Inventing the Future

One of the most profound points raised by critics like MalwareTech is the distinction between refactoring existing information and producing truly novel work. AI is essentially a high-speed blender. You put in the entire internet, and it pours out a smoothie of the most likely next tokens. It is inherently derivative. It is a rearview mirror masquerading as a windshield.

If you rely on AI to “grow” your career or your output, you are tethering yourself to the average. By definition, Large Language Models (LLMs) optimize for the most probable outcome. If you are a software engineer using AI to write your functions, you are writing the most “average” code possible. That might get the ticket closed by Friday, but it will never lead to a breakthrough. It will never lead to a new paradigm in computing or a revolutionary way to handle data.

True growth in tech comes from the ability to synthesize disparate ideas into something that has never existed before. AI cannot do this because it does not have an “internal model” of the world; it has a statistical map of human language. If you spend your formative years as a developer or a creator leaning on these tools, you are effectively lobotomizing your own ability to think outside the box. You are training yourself to be a “refactorer” of the status quo rather than an architect of the future.

The ‘Productivity Paradox’ and the Death of the Junior

We’ve all heard the phrase: “AI won’t replace software engineers, but an engineer using AI will.” It sounds clever. It’s a great line for a LinkedIn post with too many emojis. But it hides a dark economic reality. If AI increases productivity by 50%, the industry doesn’t just keep 100% of the people and do 50% more work. It shrinks the entry-level pool.

This is where the “growth” argument falls apart completely. How do you grow into a Senior Engineer? You do it by being a Junior Engineer for a few years. You do the “grunt work.” You write the unit tests. You documentation the legacy code. You do the boring stuff that builds the foundation. But now, AI is doing the grunt work. Companies are starting to realize that they don’t need five juniors if one senior with a Copilot subscription can do the output of ten.

The result? The “entry-level” bar is being pushed higher and higher. You can no longer enter the industry with just a basic understanding of logic because the AI already does that better than you. The prerequisite knowledge has grown, the pace is faster, and the stakes are much higher. We are essentially burning the bottom rungs of the career ladder and then wondering why nobody is reaching the top. This isn’t helping you grow; it’s making the environment so toxic that only those who were already experts can survive, while the next generation of talent is left “rehearsing for a world that’s disappearing.”

The Echo Chamber of Synthetic Stagnation

Let’s talk about the “Hapsburg AI” problem. As more and more content on the internet—blogs, code repositories, stack overflow answers—is generated by AI, the models begin to train on their own output. We are entering an era of digital inbreeding. If you use AI to help you write, and that writing is then used to train the next AI, the pool of human creativity starts to shrink and deform.

When you use AI to “help” you grow, you are participating in this feedback loop of mediocrity. You aren’t adding your unique, “Edan” perspective to the world. You are just contributing to the noise. In a few years, a recruiter won’t be impressed that you can generate a React component with a prompt. Everyone can do that. Your recruiter will immediately see that your work lacks the “soul” or the “novelty” that comes from human intuition. As one search finding pointed out, AI does not help you stand out. It makes you a commodity. And commodities are easily replaced.

“The true measure of intelligence should not be the ability to mimic, but the ability to diverge. AI is the ultimate mimic, and by relying on it, we are training ourselves to forget how to diverge.”

The Education Crisis: Grading the Void

Even in the realm of academia, the “AI growth” narrative is crumbling. Teachers and professors are reporting that they have no idea if their students are actually learning. When a student uses AI to write an essay on “The Socio-Economic Impact of the Industrial Revolution,” they might get an ‘A’, but their brain remains as smooth as a marble. They haven’t wrestled with the concepts. They haven’t had to structure an argument. They haven’t had to think.

This creates a generation of “Least Flourishing” individuals. We are producing graduates who have “results” but no “competence.” They have degrees, but no skills. In the tech industry, this is a death sentence. You might fake your way through an interview using a hidden window with ChatGPT, but the moment the production server goes down at 3:00 AM and the AI doesn’t have the context of your specific, messy, legacy infrastructure, you are going to drown. And you won’t have the “growth” (the mental toughness and problem-solving framework) to swim.

The Technical Debt of the Soul

In software, we talk about “Technical Debt”—the cost of choosing an easy solution now instead of a better solution that takes longer. Relying on AI is “Cognitive Technical Debt.” You are borrowing “intelligence” from a machine to pay for your current tasks. But just like financial debt, it comes with interest. The interest is the atrophy of your own skills.

Think about what happens to your ability to navigate a city when you use GPS for every single turn. After a year, you can’t find your way to the grocery store without a glowing screen telling you where to go. You have lost your “mental map.” The same thing is happening to our coding and creative abilities. We are losing our mental maps of the systems we build. We are becoming “Prompt Dependents.” If the API goes down, or if the subscription price triples, or if the model is “aligned” so much that it refuses to write certain types of code, we are paralyzed. That isn’t growth; that is a hostage situation.

Is There a ‘Wong Edan’ Way Forward?

Now, I know what you’re thinking. “Uncle Edan, are you saying we should go back to punch cards and stone tablets? You’re just an old man yelling at a cloud!”

No, you little rascals. I’m saying you need to change your relationship with the tool. AI should be treated like a calculator, not a brain. You use a calculator to do the arithmetic after you have already mastered the mathematics. If you give a calculator to a kid who doesn’t know what multiplication is, you haven’t helped them grow; you’ve ensured they will never understand numbers.

If you want to actually grow in this “AI Era,” you have to do the following:

• The 50/50 Rule: Spend at least 50% of your time working without any AI assistance. Write the code manually. Read the documentation—the actual, boring, technical documentation—instead of asking for a summary.
• Audit the Machine: Never, ever copy-paste a solution you couldn’t have explained to a five-year-old. If the AI gives you a complex regex or a recursive function, sit there and deconstruct it until you understand every single character. If you don’t, you aren’t “using” AI; it is using you to fulfill its output quota.
• Seek the ‘Hard’ Paths: Purposefully take on projects that the AI is bad at. Work on novel architectures, edge-case debugging, or human-centric UX design. The more “standard” a task is, the more the AI will eat your growth. Find the weird, the “Edan,” and the complex.
• Practice ‘Deep’ Literacy: Read books. Long ones. Physical ones. The kind that require an attention span longer than a TikTok video. Your ability to concentrate is the only thing that will separate you from the “Prompt Monkeys” of the future.

The Economic Lie of the AI Revolution

We must also look at the macro level. As Ed Zitron has argued, there might not even be a “real” AI revolution in the sense of a sustainable new industry. What we have is a massive capital injection into a technology that burns billions of dollars to save you ten minutes of typing. The “growth” promised to the economy is often just a redistribution of labor where the worker gets squeezed, the middle-man gets automated, and the value flows directly to the GPU providers.

If you base your entire career growth strategy on being an “AI Specialist,” you are betting on a house of cards. The “skills” of today—knowing how to phrase a prompt to get a specific image—are being automated by the next version of the software. It’s a race to the bottom where the “skill” disappears the moment it becomes popular. True growth is built on timeless principles: logic, empathy, communication, and deep technical understanding. These are the things AI cannot give you, and in many cases, the things AI actively discourages you from developing.

Conclusion: Reclaim Your Madness

To be “Wong Edan” is to be a bit “crazy” in the eyes of a boring, automated world. It is to insist on doing things the hard way because you know that the hard way is the only way to become a master. It is to refuse the digital pacifier that OpenAI and Google are shoving into your mouth.

AI can be a powerful tool, but it is not your friend, it is not your mentor, and it is certainly not your growth partner. It is a mirror that reflects the data of the past. If you want to grow, you have to look away from the mirror and into the unknown. You have to embrace the frustration, the bugs, the late nights, and the intellectual “struggle.”

Stop trying to be “productive” and start trying to be competent. Because when the bubble bursts—and history tells us it always does—the only people left standing will be the ones who actually know how the world works, not the ones who knew how to ask a machine to explain it to them.

Now, go turn off your Copilot for an hour and write some code that makes your head hurt. That’s the feeling of your brain growing. Don’t let the tapeworm take that away from you. Matur nuwun!