Most web developers treating AI like a magic wand are getting disappointing results. You ask for a website, get some generic HTML, and wonder why it looks like every other template on the internet.
The game changed for me when I started approaching AI like a brainstorming partner rather than a vending machine. Instead of demanding perfect output immediately, I began having actual conversations about what I wanted to build, letting each response inform the next question.
Why Your First Prompt Usually Sucks
When you tell AI “build me a landing page,” you’re giving about as much direction as telling someone to “make dinner”. Sure, you’ll get food, but it might be a sad sandwich when you wanted a three-course meal.
AI needs specifics. Not just about functionality, but about feel, audience, and purpose. Your initial prompt is rarely specific enough because you haven’t figured out what you actually want yet. Or if you have figured that out, you might not have figured out how to communicate it to the AI effectively.
Starting Broad, Then Getting Surgical
While I would normally recommend being quite specific with your first prompt, I would also advise against making it too specific. Being too specific can have unintended consequences. It can lock the AI into constraints that you didn’t intend.
I sometimes begin projects with intentionally vague prompts, just to get the creative juices flowing. Something like “create a portfolio site for a freelance photographer”. I want to see what the AI comes back with. This gives me a baseline to react against.
From that first attempt, I can see what’s missing. Maybe the color scheme feels too corporate, or the layout doesn’t showcase images properly. Or maybe the AI has created masterpiece that wouldn’t have happened if my prompt had been too specific. Either way, each observation becomes ammunition for my next prompt.
“Adjust the color palette to something warmer and more artistic. Make the image gallery the hero element, not an afterthought”.
Building Context Through Conversation
Each refinement builds on previous context. AI remembers what we’ve discussed, so I can reference earlier decisions without repeating everything.
“Keep that header design but make the navigation more subtle” works because we’ve established what “that header design” means. This conversational memory lets you iterate quickly without starting from scratch each time.
Specific Prompts Get Specific Results
Generic requests yield generic websites. But when you get granular about your needs, AI responds with much more targeted solutions.
Instead of “make it look modern,” try “use a brutalist design approach with bold typography and high contrast sections”. Instead of “improve the user experience,” specify “reduce the number of clicks needed to view the portfolio gallery”.
Yes I know I told you to start broad earlier, but I think there’s a time and place for everything. And it also depends on context. If you have specific non-negotiable requirements, then definitely state them up front. But as you refine the results with iterative prompts, you’ll need to make those prompts progressively specific in order to shape the AI’s output to the result you desire.
Testing Ideas Without Commitment
One major advantage of iterative prompting is risk-free experimentation. Want to see how your site might look with a dark theme? Ask for it. Curious about a different layout approach? Try it out.
Since you’re working with code that can be easily modified or reverted, every iteration is a chance to explore without consequences. This freedom often leads to discoveries you wouldn’t have made otherwise.
Reading AI’s Strengths and Weaknesses
Through repeated interactions, you learn what AI handles well and where it struggles. Complex animations? Usually need human polish. Clean, semantic HTML structure? AI excels here.
Understanding these patterns helps you craft better prompts from the start. You’ll ask for what AI does best while planning to handle the tricky bits yourself.
When to Stop Iterating
Perfect websites don’t exist, and neither do perfect prompts. At some point, continued refinement yields diminishing returns. I usually stop when further changes feel like rearranging deck chairs rather than solving real problems.
It could be time to wrap up when you find yourself tweaking minor aesthetic details, or you find yourself second-guessing previous decisions. It’s probably a bit much to expect AI to do everything exactly as you want it. If the site functions well for its intended purpose, then maybe you can take care of the finishing touches yourself.
Making This Approach Your Own
Every developer’s refinement process looks different. Some prefer rapid-fire iterations with small changes. Others make fewer, more substantial adjustments. Both approaches work.
What matters is developing your own rhythm and recognizing when you’re making genuine progress versus just making changes. Good iteration moves you closer to your vision, not just in a different direction.
Your website projects will improve not because you found the perfect prompt, but because you learned to have better conversations with AI about what you’re trying to build.