Vibe Code is cool, but it’s not my go‑to approach for building production‑ready apps. A few weeks ago, when Gemini 3 and GPT‑5.1 were released, I started testing different coding agents to see how powerful they had become.
The idea for this project came from a simple thought: What if I could build a collection of small, genuinely useful tools for software developers and engineers to use in their daily work? What began as a fun playground quickly evolved into a functional workspace. I started with quick, lightweight tools like a JSON formatter, text diff viewer, and QR generator. Then I pushed further to build more advanced tools like a WebP Converter and EXIF Editor.
Today, the workspace includes 25+ tools (https://devtools.henryc55.sg-host.com).
The entire project is open‑source:
https://github.com/henryphchan/dev-tools
Anyone is welcome to submit PRs, fix bugs, or add new tools, and I’ll continue expanding the collection as new ideas come up.
What is Vibe Code?
Vibe Code is a coding experience that feels like pair‑programming with an extremely fast and surprisingly capable AI engineer. You simply describe the tool you want, and the coding agent turns your idea into runnable code—often within minutes. In my own workspace (https://devtools.henryc55.sg-host.com), I use Vibe Code to build tools that help software developers and engineers with everyday tasks, all living in a single browser‑rendered environment with no backend involved. The speed and security of this setup make the development process smooth and efficient.
Build Usable tools in a minute
One of the biggest strengths of Vibe Code is how quickly it lets you create usable tools. Whether it’s converting JSON, cleaning CSV fields, or testing regex, I can go from idea to working prototype almost instantly. There’s no need for long planning cycles; I just describe the concept, let the coding agent generate the initial version, and then refine it through testing. This rapid cycle has allowed me to build a growing library of tools that genuinely make developers’ lives easier.
Easy to pass code reviews
Another advantage is how easy the generated code is to review. The coding agent usually produces readable, standardized code with clear structure, sensible variable names, predictable functions, logical flow, and well‑written comments. This makes the code review process faster and smoother, especially when collaborating with others.
The Challenges
Vibe coding sounds magical, but it doesn’t mean that everyone can build apps. Here are the three main challenges I ran into.
Challenge 1: UI/UX Limitations
Vibe coding is perfect if you don’t have strict UI requirements, just want something to function and don’t mind a generic interface. However, if you need a better user experience, the limitations show that AI is not really understand UX.
The pain points I encountered included components overlapping unexpectedly, buttons that provided no loading feedback, inconsistent spacing or styling, and user flows that didn’t feel intuitive unless manually refined. These issues happen because the coding agent simply follows your prompt; if UI/UX requirements aren’t detailed enough, it fills the gaps with generic assumptions.
Good UX requires user‑centered prompts. The more specific spacing, alignment, interactions, error handling, the better the final UI/UX.
Challenge 2: Software Design
For simple tools with a single page and a single script, Vibe Code works very well. But once a tool becomes more complex, the coding agent tends to put all the logic into one large file, skip modular design, ignore separation of concerns, and ultimately generate giant scripts that stretch into thousands of lines. This might be acceptable for quick prototypes, but it quickly becomes problematic for long‑term maintainability.
When the codebase grows too large and everything sits inside a single file, several problems begin to surface. Contributors may struggle to understand the overall structure, which slows down onboarding and makes collaboration less efficient. Merge conflicts also become more frequent because multiple people end up editing the same large file. Debugging is harder too, since tracing issues through a massive script takes much more time. In many cases, refactoring that file eventually becomes a bigger task than rewriting the tool from scratch.
The key lesson here is that while AI can generate code quickly, it doesn’t replace thoughtful software design. You still need solid engineering principles to break the system into modules, abstractions, and well‑organized components that are easier to maintain and improve over time.
Challenge 3: Bugs in Complex Tools
For simple utilities, Vibe Code works prefect, but things change once the tool becomes more advanced. Coding agents rarely get everything correct in a single prompt, especially when the logic spans multiple steps or involves edge cases. As the complexity increases, the AI difficult to produce a fully polished outcome on the first try.
The most common issues I’ve seen include incorrect handling of edge cases, inconsistent variable naming, partially implemented logic, missing validation, etc. Those errors may not very critical, but put all errors together may make the apps insecure and broken. These small imperfections remind us that AI coding agent doesn’t fully replace the need for thoughtful engineering, at least in 2026.
Through experience, I’ve learned that the best approach is to break the tool into smaller tasks and generate one component at a time. Testing frequently and iterating gradually produces the most reliable results.
The Skills Required for Software Engineers
Although AI is a powerful coding partner, the developer still plays a crucial role. Here are the skills that make Vibe coding not just efficient, but truly powerful.
Skill 1: Creativity
This is where Vibe Code truly shines. It allows you to turn ideas into prototypes instantly, experiment with different logic flows, and test multiple approaches within minutes. You can even build tools you never had time to explore before. In many ways, AI becomes your co‑worker, helping bring your ideas to life at a speed that would be impossible on your own. The only real limitation is how far your imagination can take you.
Skill 2: Software Design Principles
Understanding the fundamentals of software design—such as DRY (Don’t Repeat Yourself), object‑oriented design, the Single Responsibility Principle, modular architecture, proper error handling patterns, and clean naming conventions—plays a huge role in successful AI‑assisted development. These principles help you break down big problems into smaller, structured tasks that a coding agent can handle more accurately. Without this foundation, AI‑generated code can quickly become messy, disorganized, and difficult to maintain.
Skill 3: Code Review
AI doesn’t replace code review, and developers still need to examine the generated code carefully to ensure it meets real‑world standards. You have to look at whether it handles marginal cases, whether there are vulnerabilities, whether a simpler or more efficient algorithm exists, whether proper input validation is included, and whether the logic stays consistent from start to finish. Developers who can analyze and refine AI‑generated code will be extremely valuable in the future, as this skill becomes a core part of modern software engineering.
Takeway
- Great for scaffolding new tools
- Excellent for building fast, workable prototypes You can turn ideas into reality in minutes.
- The AI gives you a foundation but you have to refine it.
- Not a full replacement for engineering expertise
- You still need fundamental knowledge to refactor, test, structure code, ensure quality and prepare for production
- Requires developer involvement for production-ready results
- AI gets you 70–80% there. Engineers make it maintainable, reusable, and scalable.
- AI is a powerful partner. But pairing it with strong engineering thinking is essential.
And one last suggestion –
If you don’t have a tech background, you can always hire a “vibe‑coding cleanup specialist.”
They’ll clean up the AI chaos for you.