ChatGPT's Canvas mode is impressive. It generates clean, complete HTML applications right in the interface. You can see them rendered, interact with them, and refine them in real time with natural language.
Then what?
There's no "deploy" button. You can share the chat, but your guests get a code window inside ChatGPT, not a working app they can just use. There's no backend, so a form doesn't save anything and a shared list doesn't sync. And there's no access control: you can't make it private, invite specific people, or give one crowd a submit link and keep the results to yourself. To actually give it to someone, you need to copy the HTML, find hosting, add a data layer, and sort out access on your own.
The last-mile problem
This isn't a criticism of ChatGPT. It's doing exactly what it's designed to do: generate code. The problem is the assumption that code generation is the hard part.
For experienced developers, it is. They already have hosting, CI/CD pipelines, databases, auth systems. The code is the bottleneck.
For everyone else (and AI is rapidly expanding who "everyone else" means) the infrastructure is the hard part. Getting from "ChatGPT generated some HTML" to "my team can use this app" involves a dozen decisions they don't know how to make.
- Where does it live? (Vercel? Netlify? A server? Their laptop?)
- How does it save data? (Local storage only? A database? Which database?)
- Who can access it? (Everyone? Just the team? Only people with a password?)
- How do they update it? (Redeploy from scratch? Edit the source?)
What a real last mile looks like
Copy your HTML from ChatGPT. Go to ShipLock. Drop the file, set a name, pick an access policy. Done. 30 seconds, live URL, data store included, access control configured.
The AI built the app. ShipLock hosts it, stores its data, and controls who can see it. You own the URL. You own the data. Neither of those things belong to OpenAI.