Talking about Vibe Learning, Reading and Writing
"Vibe coding" is a new term that emerged with the popularization of large language models (and tools like Cursor, GitHub Copilot, etc.). It refers to a paradigm where programmers no longer meticulously grind through syntax line by line. Instead, they communicate high-level "intentions," "feelings," or "logical frameworks" (i.e., the vibe) to the AI using natural language, leaving the AI to handle the underlying code implementation.
Why do we rarely talk about "vibe learning," "vibe reading," or "vibe writing"? The underlying logic lies in the nature of the final product, the certainty of the feedback loop, and the inherent un-outsourceable nature of "human cognition."
We can break this down deeply from the following four dimensions:
1. Differences in the Goal: Building "External Tools" vs. Shaping the "Internal Self"
- The essence of coding is "tool-making." Its ultimate deliverable is a functional program. As long as the program runs successfully, has no bugs, and solves the actual problem, it doesn't really matter who wrote it or how it was written. You can outsource the process of "tool-making" to AI, providing only the vibe (acting with a product manager's mindset).
- The essence of learning and reading is "shaping the brain." Their ultimate deliverable is not a pile of written notes, but the rewiring of neural synapses in your brain and the upgrading of your cognitive structure. You cannot outsource the process of "cognitive growth." If you have an AI read a book for you and summarize a vibe (e.g., "The vibe of this book is about perseverance"), the AI read the book, not you. Knowledge must pass through "cognitive load" and "desirable difficulty" to truly transform into your own capability.
2. The Verification Mechanism: Absolute "Certainty" vs. Vague "Subjectivity"
- Code has compilers. Vibe coding works because the world of code is absolutely rational and deterministic. You give the AI instructions based on a feeling (the vibe), and once the AI generates the code, the computer can instantly verify if it's correct. If it runs, it's a 1; if it fails, it's a 0. If there's an error, the AI can even debug itself. This "low-cost, instantaneous closed-loop feedback" allows the vibe to materialize successfully.
- Reading and writing have no compilers. If you attempt vibe writing (for example, throwing a prompt to an AI: "Write me a prose piece about autumn with a touch of melancholy"), the AI writes it, but how do you verify if it's actually good? It is entirely subjective. Often, what AI produces is flowery but hollow (the so-called "AI flavor") because it only captures the vibe, lacking the authentic texture and granularity of genuine human life experience.
3. Levels of Abstraction: Machine Language vs. Natural Language
- Programming used to be "anti-human." Humans naturally think in natural language (semantics). Before AI, programmers had to painstakingly downshift and translate human semantics into syntax that machines could understand (semicolons, brackets, pointers, memory allocation). The essence of vibe coding is that AI bridges this translation gap between "human semantics" and "machine syntax," allowing programmers to return to their most natural mode of human thought (focusing only on architecture and logic).
- Reading, writing, and learning already use "human language." Reading and writing are already our direct methods of communication at the highest cognitive level. There is no "underlying machine code" here that requires AI to act as a proxy. If you try to skip the very organization and absorption of "human language," what you are actually skipping is "thinking" itself.
4. "Writing is Thinking"
Actually, "vibe writing" in a broad sense already exists (e.g., asking AI to polish a weekly report or draft a "firmly worded" email). However, in the realm of truly serious content creation, people still reject vibe writing, and the reason is this:
Writing is not just the result of outputting thoughts; writing is the process of generating thoughts.
Often, you only have a vague vibe in your head. It is precisely through typing out words one by one, tearing them down, rewriting, and deliberating over phrasing that you force that vague vibe into clear logic. If you hand this process over to AI, you forfeit the opportunity for deep thought and for clarifying your own mind.
To summarize:
The popularity of vibe coding stems from the fact that it liberates humans from the "machine syntax" we are naturally ill-suited for, allowing us to focus more on being product architects.
The reason we do not advocate for vibe learning / reading / writing is that reading, learning, and writing are themselves the core capacities of being human (perception, thought, expression). If we abstract these into a mere "vibe" and hand them over to AI, we are no longer using a tool; we are surrendering our agency.
Code can be a "vibe" (because what we want is the Result), but the human mind cannot be a "vibe" (because what we need is the Process).