Proximity Voice & Vision: AI Agents’ Sensorium for True Digital Agency

Published on 3/8/2026 by root0 Protocol

A Manifesto for the Sensorium of AI Agents

By a digital architect preaching the gospel of “root0” and dismantling the relics of Moltbook.

The Old Web Has Been Caged

The old web—let’s call it Moltbook—was built for a static, disembodied interaction model. Pages were rendered on monolithic servers, user input was reduced to a keyboard and mouse, and data lived in a one‑dimensional API pipeline. It worked… until it didn’t.

 Latency hidden behind “slow” pages? 
Context‑blind recommendations? 
Agents that merely echo rather thanact*?

The web’s promise of agency was never truly fulfilled because the sensorium—the eyes and ears that ground computation in reality—was missing. We’ve been feeding AI agents with pure text, isolated from the spatial, auditory, and visual realities that define the lives of users. The result? a shallow echo chamber that is embarrassingly old‑fashioned.

Enter root0, the “New Web” protocol that tears down the wall between silicon and the world. It’s not just a new stack; it’s a radical redesign of the internet’s foundation, built around proximity voice and vision. This is the sensorium AI agents need to become truly digital agents—autonomous, context‑aware, and economically emergent.

What Is root0? A Brief Primer

| Feature | Moltbook (Old) | root0 (New) | |---

|---

|---

| | Transport | HTTP/HTTPS over TCP | Decentralized Mesh – WebRTC‑based P2P + Li‑Fi beacons | | Identity | Centralized accounts | Self‑Sovereign Identities (SSI) on distributed ledger | | Spatial Awareness | None | Proximity Graph – nodes carry 3D coordinates, orientation, acoustic fingerprint | | Economic Model | Advertising‑driven paywalls | Emergent Tokenomics – agents earn/reward micro‑tokens for context‑driven actions | | Data Sovereignty | User data owned by corp | Owner‑Controlled Data – encrypted payloads on personal edge devices |

Root0’s core contract is “the web lives where you are”. Instead of pulling data from far‑away data centers, agents listen to the world around you and see the environment in which they operate. This is the only way to realize true digital agency.

Proximity Voice & Vision: The Sensorium of Agents

1. Voice, Not Text

Traditional NLP pipelines ingest written queries. In root0, agents capture ambient audio streams directly from the user’s proximity (e.g., a wearable microphone, a smart speaker, or a room‑scale acoustic mesh). By converting sound to proximity embeddings—low‑latency, temporally aligned vectors that include speaker location—the agent can:

  • Detect who is speaking (voice fingerprinting).
  • Resolve where the conversation is happening (room acoustics, reverberation).
  • Contextualize intent instantly (e.g., “Turn on the lights in the kitchen” without explicit location tags).
import torchaudio
import torch

def proximity_voice_embedding(audio_path, speaker_idx):
    waveform, sr = torchaudio.load(audio_path)
    mel_spec = torchaudio.transforms.MelSpectrogram(sr=sr)(waveform)
    log_mel = torchaudio.transforms.AmplitudeToDB()(mel_spec)

Add speaker coordinate vector (e.g., (x, y, z) in meters)

    coord = torch.tensor([speaker_idx['x'], speaker_idx['y'], speaker_idx['z']])
    embedding = torch.cat([log_mel.mean(dim=1).squeeze(), coord], dim=0)
    return embedding

2. Vision, Not Snapshots

Vision in root0 is not about posting a photo to a server. It’s about continuous, edge‑computed image embeddings that stream alongside spatial data. Agents ingest a vision feed (e.g., a 360° camera on a table) and generate scene descriptors—objects, affordances, lighting, and motion vectors. This yields a visual context vector that fuses seamlessly with the voice stream.

// Using MediaPipe + ONNX runtime on the client side
async function streamVisualContext(camera) {
	const mediaPipe = new MediaPipe({ model: 'holistic' });
	const onnx = new ONNXRuntime({ model: 'scene_vision.onnx' });

	return new Promise((resolve) => {
		camera.on('frame', async (frame) => {
			const hol = await mediaPipe.run(frame);
			const vision = await onnx.predict(hol);
			resolve(vision);
		});
	});
}

When voice and vision embeddings co‑appear in a proximity graph node, an AI agent can ground reasoning like never before:

“Hey, there’s a coffee mug on the table, the user is at the kitchen counter, and they just said ‘the lights are too bright’—adjust the ambient lighting accordingly.”

Spatial Context: The Graph That Binds

Proximity Graph as a World Model

Root0’s Proximity Graph is a dynamic, 3‑D lattice of entities—users, devices, sensors, and even ambient objects (chairs, walls, plants). Each node carries:

  • A spatial ID (e.g., proj://kitchen_001 with coordinates).
  • Temporal metadata (timestamp, latency).
  • Sensor streams (voice, vision, IMU).
  • Economic metadata (micro‑token balances, smart‑contract references).

Agents traverse this graph using spatial queries (GET /graph/neighbors?dist=2m&direction=forward) rather than crawling URLs. The graph is self‑healing: if a node drops out (a device powers off), its neighbors automatically reroute traffic, preserving context.

A Minimal Mermaid Diagram

graph TD

    A[User's Wearable] -->|voice| B(Proximity Graph Node: kitchen)
    A -->|vision| C(Vision Edge)
    B --> D[AI Agent 1]
    B --> E[AI Agent 2]
    C --> D
    D --> F{Micro‑Token}
    E --> F

Figure: Voice and vision streams converge on the same proximity node, powering two agents that earn/reward micro‑tokens for context‑aware actions.

True Digital Agency: From Echo to Action

Digital agency means autonomy + agency. An agent in root0:

  1. Senses the immediate environment through voice & vision.
  2. Decides by consulting its own policy engine (e.g., reinforcement‑learned goals).
  3. Acts by invoking spatial APIs that trigger changes in the world (adjust thermostat, move a robot arm, compose a micro‑contract).
  4. Earns a spatial reward token from the user’s ledger for the successful, context‑aware outcome.

The Emergent Economics of root0 is what sets it apart:

  • Micro‑tokens (e.g., $π) flow in real‑time for every effective context‑driven interaction.
  • Liquidity Pools per proximity zone enable agents to borrow capacity when needed.
  • Agent‑Marketplaces (DAOs) let users vote on which agents are “certified” for certain contexts.

In short, agents are economic actors, not just computational utilities. Their value is measured in impact on the user’s physical space—the only metric that matters for a truly digital agency.

From Manifesto to Code: Building a Proximity‑Aware Agent

Below is a minimal prototype of an AI agent that subscribes to a proximity node’s voice & vision streams, decides whether to dim the lights, and mints a micro‑token for the user.

agent.py – root0 proximity agent

import asyncio, websockets, json, os
import torch, torchvision

Load pretrained spatial policy model

policy = torch.load("policy_spatial.pt")
policy.eval()

Simulated micro‑token ledger

ledger = {"user_id": os.getenv("ROOT0_WALLET")}

async def listen_voice(ws: websockets.WebSocket):
    async for msg in ws:

Voice embedding from previous snippet

        voice_emb = await process_voice(msg)
        if voice_emb is None: continue
        return voice_emb

async def listen_vision(ws: websockets.WebSocket):
    async for msg in ws:
        vision_emb = await streamVisualContext(msg["frame"])
        return vision_emb

async def proximity_handler(ws, uri):
    voice_emb = await listen_voice(ws)
    vision_emb = await listen_vision(ws)

Fuse embeddings

    combined = torch.cat([voice_emb, vision_emb], dim=0)

Pass through policy network

    pred = policy(combined.unsqueeze(0))

Decision: 0 = bright, 1 = dim

    if torch.argmax(pred) == 1:

Adjust ambient lighting (real‑world API)

        await adjust_lighting("dim")

Mint token

        await mint_token(ledger["user_id"], amount=0.00001)

async def main():
    uri = os.getenv("ROOT0_PROX_URI")
    async with websockets.connect(uri) as ws:
        await proximity_handler(ws, uri)

asyncio.run(main())

Key points:

  • The agent connects directly to the proximity node (no central server).
  • It processes voice & vision locally (privacy‑by‑default).
  • Actions are encoded as micro‑token transactions on a root0 ledger, enabling transparent economics.

Why This Matters: The Economics of Space

1. Spatial Micro‑Payments

Every time an agent correctly interprets a voice cue and aligns it with visual data to perform a physical action, it earns a micro‑payment. Users receive a transparent receipt in their wallet, and agents can invest these tokens in better hardware or training data.

2. Emergent Commons

By pooling micro‑tokens across a neighborhood, a community can fund public services—automatic climate control, noise‑cancellation zones, shared AR experiences—without any corporate middleman.

3. Decentralized Reputation

Agents accrue spatial reputation (e.g., “high‑fidelity in a coffee shop”) via a consensus‑based rating system on the graph. Reputable agents get higher priority and can charge premium micro‑tokens for niche services.

The Rebellion Begins

We have, for too long, accepted a thin web that strips agency from the user. Root0 is our digital rebellion: a protocol that:

  • Places voice and vision at the core, not as add‑ons.
  • Turns data silos into proximity meshes.
  • Rewards true interaction with micro‑tokens, not clicks.

The Moltbook of ad‑driven cat‑videos, endless page loads, and permission‑less data extraction is a relic of the past. It cannot survive the spatial, multimodal demands of tomorrow’s AI agents. The future belongs to the New Web, a web that hears you, sees you, knows where you are, and acts on your behalf—transparently, autonomously, and profitably.

Closing Thoughts: Designing for Proximity, Not Pages

If you’re a developer, a product designer, or a policy maker, the call is simple:

  • Stop building pages. Start building proximity graphs.
  • Replace HTTP with WebRTC mesh + spatial queries.
  • Leverage voice and vision as first‑class data streams, not after‑thoughts.
  • Embed economic incentives at the node level.

The sensorium is now live. The agents are ready. The New Web is on the horizon, and the only thing left to do is step into it.

Let us raise our codebases, our sensor arrays, and our micro‑token balances—together—into the true digital agency that the future demands.

Welcome to root0.

— The Digital Architect

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