Vibe Coding Has Reached a Turning Point
I think the Vibe Coding model touches the essence of democratizing software engineering.
Put simply, software is shifting from an asset into a consumable. This shift has enormous impact on personal productivity and the software ecosystem.
First, the era of disposable software has arrived.
In the past, when we wrote code, reuse was the default assumption. Code was expensive to write. If you wrote it once and only used it once, the return on investment was extremely low.
But under the logic of AI-assisted programming, the production cost of code approaches zero. This gives birth to the idea of use-and-discard software.
For example, I now need to change the date format inside 50 filenames.
The old logic would be to find a renaming tool, or write a Python script and save it, thinking I might use it again next time.
The new logic is to ask AI to write a script, run it on these 50 files, and then delete the script. Next time a similar need appears, ask it to write a new one.
Because writing it fresh is faster than digging through old code on the hard drive or looking for a tool online. Software is no longer a product you worship and preserve. It becomes like a tissue: pull one out, use it, throw it away.
Second, only when your need is granular enough can you capture this dividend.
Many people think AI will replace programmers. In reality, AI replaces labor that can only write code but does not understand business logic.
This creates extremely high demands on the user’s product-definition ability. You need the ability to break vague desires into executable logical units.
Understanding the problem has truly become the new moat. Only people who deeply understand the essence of a problem can command AI to generate precise tools. In essence, everyone is being forced to become a technical product manager.
Third, it changes Micro SaaS and search habits.
In the past, many developers did well by building small tools such as PDF-to-Word converters, image watermark removers, and currency converters. Their business model was built on information asymmetry and long-tail traffic.
In the current era, users no longer search for these tools. They generate them directly. The value of these tools drops to zero because their functions are too easy to copy and replace. Search requests that once belonged to tool products are intercepted and digested inside the chat window.
Before, people adapted to software. We learned complex interfaces, endured unnecessary features, and paid for that one core need.
Now software adapts to people. Software is fluid and temporary. It exists only for the specific thought you have right now, and disappears as soon as it finishes serving.
This ability to generate software instantly may be the ultimate form of personal efficiency in the AI era.
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