There's a cost that shows up right after AI writes the code.
Not the debugging cost. Not the "works on my machine" cost. The one that comes even earlier, before any of that.
The deploy cost.
You prompt Claude or ChatGPT to build a landing page. It does it in 45 seconds. Clean HTML, good structure, looks exactly right in the chat window.
Then what?
For developers, this is trivial. Push to GitHub, Netlify picks it up, done. But most people using AI to build web pages right now are not developers. They are marketers running campaigns. Solo founders testing an offer. Freelancers building a quick demo for a client. No-code builders who can generate beautiful HTML but have never touched a terminal in their life.
For them, the 45-second generation is followed by a loop that looks something like this: They close the tab. The HTML never goes live.
It's a tooling problem.
The entire deploy workflow was designed by developers, for developers. Nobody designed the last mile for the person who just used AI to build something real but has no idea what Git is.
@harsh2644 wrote about the debugging tax this week: 30 seconds to generate, 5 hours to debug. That ratio is real.
But there is a deploy tax sitting right next to it. Except this one doesn't even get to debugging. It stops at "how do I put this on the web" and the answer has always been "go learn something first."
That's why I built ** HTML Deployer**, a Chrome extension that sits inside your ChatGPT or Claude tab.
It detects the HTML your AI just generated, lets you preview it on desktop and mobile before you publish, and deploys it to Netlify, GitHub Pages, FTP or your own server in one click.
No terminal. No new tab. No workflow to learn.
The generation got fast. The deploy should too.
What's your deploy workflow when you're working with AI-generated HTML?
Curious whether this is just a problem I was seeing or something others run into too.