As a developer, I always thought vibe coding was overhyped - until I actually tried it

Published Aug 2, 2026, 4:00 PM EDT Beginning his professional journey in the tech industry in 2018, Yash spent over three years as a Software Engineer. After that, he shifted his focus to empowering readers through informative and engaging content on his tech blog – DiGiTAL BiRYANi. He has also published tech articles for MakeTechEasier. He loves to explore new tech gadgets and platforms. When he is not writing, you’ll find him exploring food. He is known as Digital Chef Yash among his readers because of his love for Technology and Food. When I first started hearing people talk about vibe coding, I couldn't understand why so many developers were excited about it. The idea of describing what you wanted and letting AI generate most of the code felt completely opposite to how I'd learned software development. I always believed good developers should understand the code they write, not simply accept whatever an AI suggests. To me, programming was about solving problems, thinking through the architecture, debugging issues, and knowing exactly why a solution worked. AI-generated code seemed more like a shortcut than a better way to build software. I was also skeptical because the early AI coding tools weren't particularly convincing. They often produced code that looked correct at first glance but contained outdated practices, unnecessary complexity, or subtle bugs. Spending time reviewing and fixing AI-generated code didn't seem any faster than writing it myself. For those reasons, I ignored vibe coding for quite a while and assumed it was just another over-hyped AI trend. I tried it for small projects The biggest surprise wasn't the code quality I wasn't ready to trust AI with anything important, so I started with a few small personal projects instead. These were the kind of tasks that normally don't require much planning but still take time to build, like simple utilities, automation scripts, and small web apps. My goal wasn't to let AI do everything. I wanted to see whether it could actually speed up my workflow without creating more work later. The biggest surprise wasn't that the code was perfect; it wasn't. I still had to review the output, fix a few issues, and make changes to match what I wanted. What surprised me was how quickly I could move from an idea to a working prototype. Instead of spending time writing repetitive code or looking up syntax, I could focus on refining the feature and testing whether it solved the problem. That was the moment I started seeing why developers were embracing vibe coding. Vibe coding genuinely shines in some aspects This is where it started saving me time The more I used vibe coding, the more I realized it wasn't equally useful for every type of project. Where it really stood out was the repetitive work that most developers don't enjoy, anyway. Setting up project structures, writing boilerplate code, generating API endpoints, or creating simple UI components suddenly became much faster. Instead of spending time on routine tasks, I could jump straight to the part that actually required my attention. I also found it surprisingly helpful when learning something new. Rather than switching between documentation, Stack Overflow, and tutorials, I could ask AI to build a working example and explain why it was written that way. That made it much easier to understand unfamiliar libraries and frameworks. I still wouldn't blindly accept everything AI generated, but I found myself using it more often for tasks that were repetitive, time-consuming, or outside my usual expertise. That's where vibe coding delivered the biggest productivity gains. I realized vibe coding isn't really "coding less" AI changed my workflow, not my job The biggest shift for me was realizing that vibe coding didn't reduce the amount of thinking I had to do. It simply changed where I spent my time. Instead of writing every function from scratch, I spent more time planning features, reviewing AI-generated code, testing edge cases, and refining prompts until I got the result I wanted. In many ways, I felt more like a reviewer than a typist. AI could generate hundreds of lines of code in seconds, but it couldn't decide whether the solution actually fit my project or followed good development practices. That responsibility was still mine. I also learned that the quality of the output depended heavily on the instructions I gave. Clear prompts usually produced better results, while vague requests often led to unnecessary revisions. Vibe coding didn't replace my development skills; it relied on them. The better I understood the problem, the more useful AI became as a coding partner. What I still wouldn't use vibe coding for AI is my assistant, not my replacement Even after changing my opinion, I don't think vibe coding is the right approach for everything. I still wouldn't rely on it for projects where security, performance, or reliability are critical. If I'm building something that handles sensitive data or has complex business logic, I want to understand every important part of the code before it goes into production. I also avoid accepting large chunks of AI-generated code without reviewing them carefully. It's easy to miss inefficient logic, unnecessary dependencies, or edge cases that only show up later. AI can move fast, but speed doesn't replace careful engineering. For me, vibe coding works best as an assistant, not as a developer. It helps me write code faster, explore ideas more quickly, and reduce repetitive work, but the final decisions are still mine. That's probably the biggest lesson I learned. AI didn't replace my role as a developer; it simply changed how I approached it. I came for the hype, but stayed for the workflow Trying vibe coding didn't make me a different developer, but it did make me a more efficient one. It helped me spend less energy on repetitive work and more on building, experimenting, and improving ideas. At the same time, it reminded me that good software still depends on careful decisions, not just fast code generation. That's why I don't see AI as something to fear or blindly trust. I see it as another tool in my development workflow, much like an IDE or a debugger. My skepticism hasn't disappeared completely, but now it's backed by experience instead of assumptions.