A declarative, secure, and reactive approach to let both humans and LLMs build rich user interfaces with JSON.

The Problem with AI-Generated Interfaces

We are at an inflection point in software development. Large Language Models (LLMs) are rapidly evolving from text-generation tools into full-fledged software agents capable of building applications, analyzing data, and interacting with users in real-time. But there's a critical bottleneck: how do these agents communicate visually with humans?

The traditional options are bleak:

  1. Text-Only Responses: The chatbot experience. Great for conversation, terrible for complex interactions. Ever tried to book a flight through a wall of text? It's exhausting.
  2. Raw Code Generation (HTML/JS/React): The agent spits out code, and you hope it works. This is a massive security risk. Arbitrary code execution is the original sin of computing—do you really want to eval() whatever a cloud-based AI model sends you? The answer is no. And, the flexibility of raw language generation can result in either too much brittle code or too much variance from UI exprience to UI experience, something humans do not handle well.

The probable end states are far away:

  1. Direct generation of images and video with which users can interact in real-time is too expensive and slow.
  2. Direct mind interfaces are not yet possible except for the simplest of tasks. Google recognized the traditional options gap and perhaps the distance to an ultimate end-state when it introduced A2UI (Agent-to-User Interface) in late 2025. It's a declarative JSON format where agents describe UI components like text_field or button, and client applications render them natively. It's a solid approach with a security-first architecture.

And, I asked additional questions:

This is why I built cDOM (Computational DOM) and its expression language, JPRX (JSON Pointer Reactive eXpressions).

Let me show you how it works, step by step.

Step 1: A Reactive UI with Zero Server Code or Custom JavaScript

Consider a simple counter. In cDOM, you write JSON with embedded JPRX expressions like this:

{
  "div": {
    "onmount": "=state({ count: 0 }, { name: 'local', scope: $this })",
    "children": [
      { "p": ["Count: ", "=local/count"] },
      { "button": { "onclick": "=local/count++", "children": ["+"] } }
    ]
  }
}

That's it. No server. No round-trip. No JavaScript except the underlying cDOM library (which could be JavaScript, Dart or some other language).

The entire UI is reactive, self-contained, and runs instantly in the browser.

This is the spreadsheet paradigm applied to UI: you define the relationships, and the system handles the updates. As you will see below, similar to a spreadhseet, JPRX has over 100 helper functions, covering everything from math and string manipulation to complex array processing.

Step 2: But What If You Do Want LLM Integration?

The counter example is great for client-only interactions. But what if you want to notify an LLM (or any server) when the user clicks a button?

Just swap the operator for a =fetch helper:

{
  "button": {
    "onclick": "=fetch('/api/notify', { method: 'POST', body: $event })",
    "children": ["Notify LLM"]
  }
}

When the button is clicked:

  1. The =fetch helper sends a POST request to /api/notify with a JSON body.
  2. Object bodies are automatically stringified, and Content-Type: application/json is set for you.
  3. The LLM (or your backend) receives the event and can respond however it likes.

This is the event registration model: the LLM doesn't need to be notified of every interaction. It only hears about the events that matter—the ones where you've wired up a fetch. Developers can wire up fetch to any event they want, or when LLMs generate a cDOM component, they can wire up fetch to notify them of specific user actions.

This avoids the potential chatty nature of A2UI. Do you really want the LLM notified of every mouse move? Keyboard stroke? Scroll position? Is it time and cost effective to have an LLM deal with things like sorting and filtering, or should you let the client handle it?

LLM-driven architecture. Native-like responsiveness.

Step 3: What If the LLM Wants to Modify the UI?

Here's where cDOM gets truly powerful. What if the server (or LLM) wants to push a new component into the page?

Enter =mount:

{
  "button": {
    "onclick": "=mount('/api/get-widget')",
    "children": ["Load Widget"]
  }
}

When clicked, mount fetches JSON from /api/get-widget, hydrates it as a reactive cDOM element, and appends it to the document body.

But wait, what if the LLM wants to place that widget somewhere specific, like a sidebar? That's where move comes in.

The LLM simply includes a =move directive in the component it returns:

{
  "div": {
    "id": "weather-widget",
    "onmount": "=move('#dashboard-sidebar', 'afterbegin')",
    "children": ["Sunny, 75°F"]
  }
}

Here's what happens:

  1. mount fetches the widget and appends it to the body (a "safe landing").
  2. The moment the widget mounts, move rips it out and teleports it to #dashboard-sidebar.
  3. If a widget with the same id already exists there, it's replaced - making the operation idempotent.

The LLM doesn't need to regenerate the entire page. It just pushes components that know how to place themselves.

The Full Picture: Three Levels of Power

You've now seen the three core capabilities:

Level

Use Case

Helper

Server Involved?

1

Client-only reactivity

=state, =++, etc

❌ No

2

Notify LLM of user actions

=fetch

✅ Yes (one-way)

3

LLM pushes new UI to the client

=mount, =move

✅ Yes (returns UI)

This layered approach means you can build:

All with the same declarative JSON format.

JPRX: The Expression Language Behind the Magic

You've been looking at JPRX expressions above. Let me explain what's under the hood.

JPRX (JSON Pointer Reactive eXpressions) is an extension of RFC 6901 JSON Pointer. It adds:

Why is this perfect for LLMs?

  1. Context-Free Grammar: No closures, no callbacks. An LLM generates JPRX as easily as it generates a sentence.
  2. Safe by Design: No access to globalThis, eval, or the DOM API outside registered helpers. The application developer controls the helper catalog.
  3. Streamable: The LLM can stream components one by one. Each piece is self-describing and self-mounting.

And why is it great for human developers? Because JPRX reads like a spreadsheet formula. If you can write =SUM(A1:A10), you can write =sum(/cart/items...price).

Head-to-Head: cDOM vs. A2UI

Feature

cDOM/JPRX (Lightview)

A2UI (Google)

Core Paradigm

Declarative + Reactive Computation

Declarative Description

Client-Side Reactivity

✅ Built-in via signals & computed expressions

❌ Requires server round-trip for state changes

Interaction Model

✅ Handlers execute client-side (low latency)

⚠️ Every interaction signals back to agent (chatty)

Security Model

✅ Sandboxed helper functions, no arbitrary code

✅ Sandboxed component catalog, no arbitrary code

Expression Language

✅ Full formula language with 100+ helpers

❌ Data binding only, no computation in the format

LLM Streaming

✅ Components self-mount & teleport via =move

✅ Flat component list with IDs for incremental updates

Two-Way Binding

✅ =bind(/path) for inputs, selects, checkboxes

⚠️ Component-specific, varies by renderer

State Management

✅ Scoped, schema-validated state objects

❌ External state managed by agent or backend

Framework

Lightview (Vanilla JS, ~5KB core)

Client-agnostic (Flutter, React, Angular renderers)

A2UI is an excellent wire format for describing static snapshots of a UI. It fits neatly into enterprise ecosystems where Flutter or Angular applications render components.

cDOM is designed for dynamic, client-reactive applications where the UI is a living computation. When your LLM generates a dashboard, you want it to react to user input—filter, sort, calculate—without a server round-trip for every interaction.

And while the current reference implementation is in JavaScript, nothing prevents cDOM and JPRX from being implemented in other languages like Dart or Swift. The core concepts—reactive pointers, helper functions, and declarative structure—are universal. You could build a Flutter renderer for cDOM just as easily as Google built one for A2UI.

Custom Components: Extending the Vocabulary

A powerful feature of A2UI is capability negotiation: the agent queries the client's component catalog before generating UI. This ensures compatibility across different renderers.

cDOM takes a different approach. There's no formal negotiation protocol, but the ecosystem makes adding custom components trivial.

Libraries like Lightview and Juris.js allow you to define custom HTML elements:

const MyButton = () => {
  return {
    button: {
      style: 'font-size: 25px'
      children: ["My Button"]
    }
  }
}

The above is trivial for this example. Far more complex elements can be defined and once defined, these elements are immediately usable in cDOM:

{ div: 
  { 
    MyButton: {
      onclick: "=fetch('/api/notify', { method: 'POST', body: $event })"
    }
  } 
}

The above would render as:

<div onclick="<compiled handler>"> 
  <button style="font-size: 25px">My Button</button> 
</div>

The philosophy: the application developer controls the component catalog, just as in A2UI. The difference is that cDOM skips the negotiation handshake—the LLM uses components it's been trained to expect for that application. If discovery is needed, a JSON manifest of available components can be provided to the LLM as context.

This trade-off prioritizes simplicity and low overhead for applications where the component set is known in advance - which is true in many situations.

Why This Matters for the Future of Agentic UI

I believe the next wave of applications will be agent-first. Not chatbots with UI bolted on, but intelligent systems where conversation and application dissolve into one.

A user might ask:

"Show me my sales performance for Q4, highlight anything below target, and let me drill down by region."

An LLM should respond not with a paragraph, but with a live dashboard: a chart that filters, a table that sorts, a summary that recalculates. When the user says "focus on EMEA," the agent streams a UI patch that updates the view in place.

cDOM and JPRX could be the foundation for this vision:

Get Started with Lightview

cDOM and JPRX are part of Lightview, a reactive UI library combining aspects of Bau.js, Juris.js, and HTMX with a router and cDOM. It's browser-native, and designed for both humans and machines.

cDOM is currently in experimental preview and could easily be implemented outside the scope of Lightview. I'm actively refining the expression language and helper library based on real-world use cases. I'd love your feedback.

Conclusion: The Spreadsheet Moment for UI

Spreadsheets democratized computation. You didn't need to be a programmer to define that C3 = A1 + B2 and have it update forever.

cDOM is designed to be that moment for user interfaces. A format where an LLM—or a human—can declare: this text shows the count; this button increments it; this chart sums the sales. And the system handles the rest.

In a world where AI agents are becoming the new developers, the language they speak to the browser matters. I think that language should be safe, reactive, and computational from the ground up.

That's cDOM. Welcome to the Computational DOM.