👋 The Backstory
I want to share a recent "experimental project" of mine: HardwareTest.org.
The motivation was simple: I bought some new peripheral...
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This is so true because AI does not have the capability to think and and give you a 100% fully functioning code. If you do not have some sort of knowledge yourself, it would blindly lead you into creating something that simply doesn't work (the way you would want it to). Good read 👍
Exactly! It feels like working with a super-fast junior developer who is extremely confident but often wrong. 😂
If I didn't have a basic understanding of how the browser Event Loop or DOM listeners work, I probably would have given up when the keyboard test failed initially. You definitely need to be the "pilot" to verify where the AI is taking you. Thanks for reading!
Vibe Coding is like a slot machine; it consumes a lot of Tokens and you might win, or you might not.
The biggest drawback of generative AI is that it guesses the most suitable words from a database - it can't think, which makes its answers to very complex questions seem illogical and limited. Therefore, AI is far from perfect.
That explains the "hallucinations" I encountered perfectly.
Like you said, it was just guessing the most suitable syntax patterns for the SEO schema. It looked like valid code because the words were right, but the underlying logic was completely broken because it couldn't "think" through the structure. It’s a probabilistic engine, not a reasoning one.
When someone says "vibe coding", they mean the new agentic type not that one in which you would ask the AI and copy the code and paste manually and then continue the chat in the same way and what I experienced in the new agentic type is that it is so bad than the type described above I mean they make so much errors and often superficial comments and in reality not in the same way while the manual method is much powerful than the agentic one even though it would slightly cost more time but still better. Did you experience this also?
100% experienced this. You hit the nail on the head.
I found that the "manual" copy-paste method acts as a necessary Human Code Review layer. When I let the "agentic" features (like auto-apply in IDEs) take over, they often introduced subtle regressions or broke things elsewhere that I didn't notice immediately.
Copy-pasting forces me to read and understand the logic before committing it, which saved me multiple times when the AI tried to use non-existent APIs for the keyboard test. The "extra time" is actually "safety time."
The Agentic AI is built for tasks like web development, mainly HTML, CSS, and JavaScript. If you go beyond that, such as using a different language or working on a complex project, the AI will first tell you it’s not feasible. And even if it does try to implement it, the result will have thousands of errors, to the point where you’ll wish you had written the code yourself. At that stage, you realize it’s easier to code it on your own than to fight the AI through hell especially the Agentic AI and the manual method is a bit powerful because you control and ask what to add or to code next etc.
Easier to code it on your own than to fight the AI" — I felt that in my soul. 💀
Even within JavaScript (which it's supposed to be good at), as soon as I stepped outside standard DOM manipulation and tried to implement the 1000Hz polling algorithm, the Agentic AI completely lost the plot.
It kept aggressively applying "fixes" that introduced race conditions I didn't have before. I eventually had to stop the agent, revert the files, and manually guide it logic-block by logic-block. The "manual method" is basically damage control
For me, AI is a tool, and also an assistant, a teacher, sometimes even a mentor.
It’s not there to replace us or do the work for us.
When you learn how to use it well, it removes friction, sharpens your thinking, and helps you move much faster.
In that context, yes, you can easily go ten times quicker, but not because it thinks better than we do, but because it expands what we can do.
I love the "teacher" perspective. Ironically, it taught me the most when it got things wrong (like the Polling Rate logic).
By giving me a solution that almost worked, it forced me to dig into the browser's Event Loop documentation to understand why it failed. So in a way, it did sharpen my thinking, just not by giving me the answer, but by pointing me in a direction to explore.
Great!