A few days ago, a friend who had previously highly praised and fully embraced Vibe Coding posted a tweet expressing his recent frustration with AI-based programming:
“Recently, Vibe Coding hasn’t brought me any joy in writing code. On the contrary, I’ve felt frustrated by AI’s inability to get things right the first time. I’ve started reading official documentation and quality videos again, building knowledge from the ground up, and that sense of control over my projects has returned.”
I believe this sentiment resonates with many developers. Today’s large language models often demonstrate astonishing capabilities in areas we’re less familiar with, leaving a profound first impression that creates unrealistically high expectations. However, with deeper use, we gradually discover that AI’s limitations are far more significant than we initially imagined.
All along, I’ve limited AI’s role in my programming to specific areas: generating and refining documentation, optimizing code at the function level, and helping me understand and learn unfamiliar frameworks and technical details. Even with these constraints, the efficiency gains that AI brings remain impressive. More valuable still is that with AI’s assistance, I can feel my skills continuously improving, and this growth gives me confidence in mastering technology.
Thinking back to the social panic triggered when ChatGPT first appeared (fears of human replacement leading to massive unemployment), these predictions haven’t materialized. Instead, as people’s understanding of AI’s capabilities and limitations has become clearer, the focus has shifted to how AI can assist human work rather than completely replace it. AI, like all tools throughout human history, is essentially an extension of human capability. If you’re experiencing difficulties using it, perhaps you should reflect on whether your approach to viewing and using it is appropriate.
“Enjoy the vibe, but don’t get lost in it.” While Vibe Coding as an emerging programming paradigm certainly makes programming more efficient and enjoyable, it shouldn’t become an excuse for abandoning deep learning and understanding of technology. We should view AI’s capabilities rationally, improving efficiency while not forgetting the original intention of technical excellence. Perhaps in the future, AI may replace us in “typing” code, but we must retain the initiative in thinking and creativity.
