Why did the expert succeed in generating a website with AI, while the beginner failed?
AI website generators (Bolt.new, Framer AI, Wix AI, Durable, ChatGPT, etc.) still don't allow beginners to "magically" get a working website without additional work and knowledge. The key reasons for failure are the limitations of AI, poor task formulation, and lack of basic user skills.
First, AI systems often give inaccurate or outdated solutions because they don’t fully understand context. They can confidently "hallucinate" incorrect code without alerting the user.
Second, AI can’t run the code or fix resulting errors on its own – this still requires knowledge of development environments and build tools. Without the proper setup (correct library versions, bundlers, configurations), even generated HTML/CSS/JS code might not work.
Moreover, many beginners underestimate how much work still falls on them: manual debugging, testing, and code refinement are required. According to experts, even with well-formed prompts, the final code always needs to be thoroughly reviewed and tested.
Finally, tools like Bolt.new and other AI-based web service generators have technical constraints: limited context, reduced performance, and narrow-domain knowledge. In longer dialogues, the model may “forget” earlier decisions and overwrite them.
Prompt Formulation Errors
Failures often begin at the communication stage with AI: the prompt is too vague, incomplete, or poorly structured. Beginners may ask, “Create a website for a business” without details, causing the AI to return a template that doesn't reflect real requirements. To get a relevant result, the task must be described in detail: what should be on each page, what technologies and styles to use, what elements need to function (forms, galleries, etc.).
Habr recommends including the task goal, environment, functional requirements, examples, and output format in the prompt. For example, instead of the vague “Write a data saving function,” it’s better to provide a clear description of the API, fields, validation rules, and error handling. Otherwise, the result will be fragmented and useless.
Also, it’s important to specify libraries or frameworks (Bootstrap, Tailwind, React, etc.): the more info the model receives, the more accurate the code will be. Furthermore, break down the task into steps: first ask for a plan or website sketch, then generate code for individual components. Ineffective prompts are “boilerplate” phrases without context (e.g., “add some text here”). Without detailed instructions and a sequence of actions, the AI will either return a basic “skeleton” of a website or entirely inappropriate code that will require heavy reworking.
Mistakes in Using Generated Code
Even after receiving the code, beginners often misuse it. A typical mistake is copying and pasting code without verification. Users may paste AI responses into an editor and run them without starting a local server or installing dependencies. This leads to compile-time or browser errors. Experienced users note that “instant copy-paste of code” is a guaranteed path to issues.
For example, the model may generate a React component without importing required modules: if those modules are missing, the code simply won’t compile. Another common error is trying to update an entire website with a single prompt. Beginners often paste the whole project into the chat, ask to “update the page,” and the AI makes numerous small changes, often breaking previous settings. The result is unreadable code. It's better to work in parts: copy a single file or code block into the chat, ask for changes, test them, and then move on to the next part.
In addition, many users lack experience with IDEs and version control systems. Forum users recommend not editing a website in a plain text editor but using a full development environment (like VS Code) and Git. This helps track changes: AI may accidentally add “extra” code or delete important parts, and without version control it’s difficult to revert. Also, always test code in the browser and developer tools: AI often misses small syntax errors or typos (e.g., variable name mismatches, unclosed tags, etc.). That’s why it’s advised to run the code through tests or validators and conduct a manual review after generation.
Lack of Understanding of Web Architecture and Tech Stack
Many failures occur because beginners lack foundational knowledge of HTML/CSS/JS and the website build process. They don’t know the difference between static and dynamic sites, or how styles and scripts are connected. As a result, the generated code often doesn’t “come to life” immediately.
For example, ChatGPT may generate several files (index.html, style.css, script.js), but the user forgets to link them (correct paths), or doesn’t realize that a local server is needed for import/export modules in JS. Similarly, many are unaware of automated bundlers (Webpack, Vite) and package managers: without commands like npm install and npm run build, no React/Vue project will work.
Experienced community members point out that working with code requires basic knowledge: at the very least, understanding HTML structure, CSS styling, and how JS works in the browser. Knowledge of responsive design, layout principles, flexbox/grid is especially useful. Without this, the final site may either “jump” when resizing the window or look broken. WPZoom emphasizes: “you’ll need technical skills to use all that code and customize the site to your needs.” Otherwise, beginners simply won’t understand how to refine the AI-generated features.
Not understanding architecture also means not knowing deployment steps. Many assume it’s enough to upload the generated HTML to a hosting platform, but often additional files are needed (favicons, JSON data, server config). Without skills in deployment, SEO, or meta-tag setup, the site won’t function properly in production. As a result, a beginner takes the AI code, tries to run it “as-is,” and encounters countless small build and configuration issues.
Psychological Traps
There are several psychological factors that hinder beginners. First is overtrust in AI: the model “speaks” confidently, and many take its code at face value. As seen in various case studies, ChatGPT often gives confident answers even if they’re wrong. This AI “perfectionism” misleads users: it’s hard to suspect an error if the model doesn’t signal anything.
Second, many expect a “miracle.” They wrestle with complex architecture problems but simultaneously expect AI to handle everything. This leads to disappointment: “if ChatGPT didn’t generate a complete website in one prompt, something’s wrong.” Community members advise: “learn programming basics first” and don’t rely solely on AI. Without understanding core concepts (loops, functions, routing), it’s hard to assess the result and spot model mistakes.
Beginners also suffer from confirmation bias: they seek validation from AI and miss discrepancies. As noted in a discussion, this is a dangerous trap: you shouldn’t blindly trust results that reinforce your beliefs. For instance, if the model generates outdated React code (using instead of in newer versions), an inexperienced user might not notice the mismatch and end up with a non-working site.
Lastly, suppressed initiative: many beginners are ready to trust the AI “entirely,” without trying to understand things themselves. This leads to no learning from their own mistakes. It’s important to understand that AI is a tool for accelerating work and learning – not a replacement.
As experienced developers suggest, you can’t just “sit and let the AI write code” – you need to analyze the results and manually correct them.
Recommendations and Tips
1. Clear and Detailed Task Description When working with AI generators, it’s important to create structured prompts. The recommended formula: goal + context + requirements + examples + constraints + output format. For example: “Create a responsive HTML homepage for a photo studio website. The page should have a header with a menu (‘Home,’ ‘Portfolio,’ ‘Contact’), a main section with a gallery of 6 placeholder images, an ‘About Us’ section with text, and a footer with a newsletter subscription form.”
Such detailed description helps the AI understand which elements and styles are needed. Specify technologies (“using Bootstrap 5” or “CSS Flexbox”), screen sizes (mobile/desktop), and the desired format (code only or with comments).
2. Iterative Approach and Templates Don’t try to get the entire website in one request. Break the task into stages: first get the HTML template (structure), then generate CSS and JS separately. Ask the AI for a plan or pseudocode first, approve it, and then move on to writing code. When facing issues, ask the AI to “rewrite the component differently” instead of endlessly fixing the same version. It’s also helpful to insert your previously generated code into the prompt and ask for specific edits.
3. Use UI Libraries and Templates To avoid writing everything from scratch, use well-known frameworks. In your prompts, include: “generate a website using Bootstrap (or Tailwind, Material UI, etc.).” The AI can generate code with these libraries in mind, greatly simplifying the process. Also, you can use ready-made HTML templates. For example, find a suitable template on HTML5 UP or ThemeForest, copy its structure, and ask the AI to adapt or expand it for your needs. This helps avoid basic layout and design mistakes.
Even if you’re a beginner, you can still copy-paste a UI element from these template libraries to start.
4. Manual Code Review and Refinement Generation is just the first step. Experts recommend that you manually test the website after receiving the code. Open pages in the browser, use dev tools to debug, run tests. If there are errors, give the AI those exact error messages – the model can often suggest fixes based on them. Always read and understand the generated code, and correct any inaccuracies (update libraries, fix paths, remove unnecessary elements).
5. Learn the Basics of Web Development The shortcut to using AI tools successfully is understanding the fundamentals: HTML structure, CSS styles, JavaScript behavior, and site build processes. Even a basic grasp of how scripts and styles are linked, what meta tags do, routing systems, and build steps will help you spot AI mistakes and avoid common pitfalls. As experienced developers advise, study simple sites manually first (e.g., build a one-page site or blog using a tutorial) – this will help you ask better questions and understand AI’s answers. With this approach, you’ll act not as a “chat operator” but as a collaborative coder.
6. Alternative Tools and Platforms For full confidence, beginners can temporarily switch to simpler solutions. Website builders (Wix, WordPress, ready-made AI platforms) allow you to quickly get a site with minimal knowledge.
If you have little to no web development experience, it’s better to use beginner-friendly platforms or template sites. Once the site is created, you can gradually dive into the code or learn through AI-assisted development. This hybrid approach provides a working result and helps build knowledge without critical mistakes.
These recommendations are based on expert articles, practitioner feedback, and real-life cases of using AI website generators.
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