Something changed in how I use AI tools about three months ago.
I stopped asking "can AI do this?" and started asking "how many steps does it take to go from AI output to something I can actually use?"
That question changed everything.
The output is not the product
When ChatGPT or Claude generates something for you, what you get is raw material. Not a finished thing. Raw material.
A developer gets code. They still need to run it, test it, debug it, deploy it.
A marketer gets HTML. They still need to put it somewhere, get a URL, send it to someone.
A founder gets a landing page. They still need to figure out hosting, domain, publish flow.
The AI part is fast. Genuinely, impressively fast. 45 seconds for a complete HTML page is real and it matters.
But we got so excited about the 45 seconds that nobody counted what came after.
I counted
Here is what it actually takes to go from "Claude gave me an HTML file" to "I have a live URL I can share" using the default workflow most people end up with.
- Copy the HTML from the chat
- Open a new tab
- Create or log into a Netlify account
- Find the deploy option
- Save the HTML as a file locally
- Drag the file into Netlify
- Wait for deploy
- Copy the URL
- Realize the URL is something like rainbow-unicorn-a3f92.netlify.app
- Go back and configure a custom domain
- Wait for DNS propagation
That is eleven steps. Eleven steps between a finished AI output and something a real person can open on their phone.
Some of those steps take 30 seconds. Some take 20 minutes. Some fail and send you back to step 4.
The AI saved you 2 hours of writing and design work. The deploy process took 45 minutes on a good day and 3 hours when something went wrong.
The honest math
People talk about AI productivity in terms of what it generates. Nobody talks about the total workflow.
Total workflow = generation time + everything after
For a developer, "everything after" is second nature. Git push, CI/CD picks it up, done. The steps are invisible because muscle memory made them disappear years ago.
For everyone else, every single step is visible, unfamiliar, and potentially a dead end.
This is the real productivity gap. Not whether AI can write good code. It can. The gap is between the output and the outcome.
What I actually changed
I started optimizing for step count, not generation quality.
A slightly worse output that takes 2 steps to use beats a perfect output that takes 11 steps every time.
That thinking led me to build HTML Deployer, a Chrome extension that cuts the HTML-to-live-URL flow from 11 steps to 3.
- Step 1: the extension detects the HTML Claude or ChatGPT just generated, no copy-paste.
- Step 2: you preview it on desktop, tablet, and mobile before anything goes live.
- Step 3: you pick a target, Netlify, GitHub Pages, FTP, or your own server, and click deploy.
That is it. You never leave the tab. You never touch a terminal. You never save a file.
The generation is still 45 seconds. The deploy is now under 60 seconds too.
The question worth asking about every AI tool
Before you add another AI tool to your workflow, count the steps between its output and something you can actually use.
If the answer is more than 3, the tool is probably not saving you as much time as the demo suggested.
The AI part of the problem is mostly solved. The handoff part is where the time is actually going.
How many steps does your current AI-to-live workflow
take? Curious whether the 11-step version I described
is common or whether people have found shorter paths
I haven't seen yet.
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