A few months ago I would open a new project, spend the first hour setting up boilerplate, wiring authentication, and configuring the database before writing a single line of actual product logic. Now I describe what I want in a prompt and half of that setup is done before my coffee gets cold. That shift has a name now. Everyone calls it vibe coding.
The term was popularized by Andrej Karpathy and it went on to become the Collins Dictionary word of the year. What started as a joke about "vibing" with an AI while it writes code has turned into one of the most debated shifts in how software actually gets built. Some developers treat it as the biggest productivity unlock of the decade. Others treat it as a shortcut that is quietly filling production codebases with fragile, unreviewed code. Having built and shipped several real products this year using AI heavily in the loop, I think both camps are partly right and both are missing the actual point.
What vibe coding really changed
Vibe coding is not about typing less. It is about where your attention goes. Instead of spending mental energy on syntax, boilerplate, and remembering an API signature you looked up five times last month, you spend it on intent. You describe the outcome you want and the AI handles the translation from idea to code. For someone building a SaaS product on their own, this is not a small convenience. It is the difference between shipping a feature in an afternoon and shipping it over three days.
I have felt this directly while building an image editing platform with dozens of tools on the frontend and backend. Features that used to mean digging through documentation for an hour now start as a plain description of what the tool should do, and the first working draft is ready before I have finished thinking through the edge cases. That is real leverage. Pretending otherwise is dishonest.
Where it quietly breaks
Here is the part most hype articles skip. AI generated code is only as good as the context and constraints you give it, and even with a well written prompt, the output still needs a human who understands the system to check it. I have caught race conditions, missing validation, and quietly duplicated logic in AI generated code that looked completely correct on the surface. None of that is a flaw unique to AI. It is the same category of mistake a junior developer makes when they copy a pattern without fully understanding why it works. The difference is that AI can produce that mistake at a speed and volume no junior developer ever could.
Recent industry surveys back this up. A meaningful share of AI generated code still ships with vulnerabilities when nobody reviews it carefully, and the developers who get real value from these tools are consistently the ones who treat AI output as a first draft rather than a final answer. Vibe coding does not remove the need for code review. If anything, it makes code review more important than it has ever been.
The skill that actually matters now
The developers thriving with this shift are not the ones who prompt the fastest. They are the ones who can read AI generated code and immediately tell whether it is structurally sound. That skill did not exist as a formal discipline two years ago. It is closer to editing than writing. You are not typing every line anymore, but you are still fully responsible for what ships, which means your ability to spot a bad abstraction or a missing edge case matters more than your typing speed ever did.
This is also why I think the developers who are worried about becoming irrelevant are asking the wrong question. The question was never whether AI can write code. It clearly can. The real question is whether you can still tell good code from bad code once it is written for you instead of by you. That judgment is the actual skill, and it is built the same way it always has been, by reading code, breaking things, and fixing them yourself long before AI became part of the workflow.
How I actually use it day to day
My workflow now looks less like writing code from scratch and more like directing a very fast, very literal collaborator. I describe the feature with enough detail that there is no ambiguity about the tech stack, the expected behavior, and any constraints that matter. I let the first draft come back quickly. Then I read it the same way I would review a pull request from a teammate I do not fully trust yet, checking assumptions, tracing the logic, and testing it like a user would before I ever consider it done.
That last step is the one people skip when they get excited about speed. Shipping fast only matters if what you ship actually works. The teams and individuals getting burned by vibe coding right now are almost always the ones who skipped verification because the output looked plausible. Plausible is not the same as correct, and in software those two things diverge more often than anyone wants to admit.
Where this is heading
Vibe coding is not a passing trend and it is also not the end of traditional programming knowledge. It is a new layer on top of skills that still matter. Understanding architecture still matters. Understanding why a database query is slow still matters. Understanding what happens when ten thousand users hit your API at once still matters just as much as it did before any of this existed. What changed is how much of the repetitive, low judgment work now happens automatically, freeing up time for the parts of engineering that actually require a human brain.
If you are a developer trying to decide how seriously to take this shift, my honest answer is to stop treating it as a debate about whether AI belongs in your workflow. It already does, whether you invite it in deliberately or not. The real decision is whether you are going to be the developer who lets it write code you do not understand, or the one who uses it to move faster while staying fully in control of what gets shipped. Only one of those approaches survives contact with a production incident at two in the morning.
