The model that writes a page shouldn't be the one that signs it off

My name is Hrithic Rajpurohit, and I work on the engineering team at Produsa Labs. We built Produsa, an AI website builder made for India, so I should tell you that before I describe how the build pipeline works.

A website build is not one task. Research, brand, copy, layout, code and a final check all ask different things of a model. If the whole job goes through a single model, the writing, the design sense and the engineering quality all settle at whatever that model is average at.

Produsa instead sends each job to the model that does it best. The ones we use are Claude, OpenAI, Gemini, xAI/Grok and Kimi. We have not published a map of which model takes which step, so I will not invent one here. The useful part is the idea: pick the model for the job, not one model for the whole product.

We also added a second, separate pass. After a page is written and designed, a different AI reviews it against a written design rulebook. The first pass can look finished and still miss the brief, repeat a layout, or drift from the brand. That review only works if the rulebook is specific enough to fail. A vague "make it look good" rule just gets a yes.

What I would tell another team doing this: write the bar down before you hook up the reviewer. If the only standard lives in someone's head, the review pass has nothing firm to argue with.

If you have tried a reviewer model on generated UI or copy, I am curious what you put in the rulebook, and what it still lets through.

This article was drafted with AI assistance and then checked by me. I can stand behind the facts above.