Turning documentation into a working AI assistant - no engineers required

A lot of founders and creators want to build AI assistants — not ChatGPT clones, but domain-specific helpers:
career advisors, fitness guides, teaching bots, project management assistants, etc.

But when I watched people trying to build them, the real problem wasn’t the AI.

It was the blank page.

They didn’t know:

• how to structure a prompt

• what instructions the model needed

• how to teach it using documentation

• how to make the output consistent

• how to ship it as an actual app

So instead of building “another chatbot,” I built something more useful:
a workflow that turns your documentation into a functioning RAG-based AI assistant inside Fuzen—without any traditional development.

Video walkthrough:

The core idea

Your knowledge lives in documents.
Your assistant should be built from those documents, not from thin air.

So the workflow I built does this:

• Upload your domain knowledge (examples, specs, definitions, instructions)

• OpenAI’s file-search assistant becomes the “brain”

• Fuzen provides the UI + logic

You get a working assistant that can:

• answer questions based on your docs

• produce structured outputs

• generate app prompts

• support multiple threads

• adapt to any niche you feed it

Everything else — routing, UI, chat handling, threads — is already handled.

What I built behind the scenes

Instead of writing code, I wired up a workflow where you:

• Install a pre-structured app shell (think of it as the frame).

• Create an AI Assistant on OpenAI and feed it the exact documents you want it to reason with.

• Paste two fields — API Key and Assistant ID — into a settings page.

• Start interacting with a functioning RAG model immediately.

It feels less like “building software” and more like “connecting your knowledge to an interface.”

What it can actually do

If your documentation is good, the assistant can produce highly structured, highly useful outputs.

In the demo, I asked:

“Write a prompt for a real estate CRM.”

The response wasn’t a paragraph.
It was an entire app blueprint:

• Data model

• UI layout

• Pages

• User flows

• Styling instructions

Copy → paste → generate an app.

This changes how people prototype software — you don’t refine ideas verbally; you refine them through doc-driven AI.

Adapting it to your niche

Because the UI lives on Fuzen, it’s fully modifiable:

Want your brand colors?
Ask Fuzen AI to restyle it.

Want file uploads, voice notes, or custom workflows?
Ask Fuzen AI to add components.

Want to make it a paid standalone SaaS?
Add authentication + payments.

The AI assistant is powered by your documents, but the app hosting it is flexible.

The real insight

People don’t struggle to build AI assistants because of the technology.
They struggle because they don’t know how to encode their expertise into a system.

The moment the assistant starts referencing real documentation, everything changes:

• responses become consistent

• outputs become structured

• hallucinations drop