Web4: The Symbiotic Agentic Web

0. Solid Pods: The Foundation of True Data Sovereignty

Solid Pods (Personal Online Datastores) are secure, decentralized personal data stores that put users in full control of their information. Created by Sir Tim Berners-Lee (inventor of the World Wide Web) in collaboration with MIT starting around 2016, and advanced commercially through Inrupt (founded 2018), Solid reclaims the web's original vision of empowerment by decoupling data from centralized applications and platforms.

Solid solves critical problems of the modern web: centralized data silos (e.g., controlled by Google, Meta, etc.), privacy erosion through unchecked harvesting and surveillance capitalism, lack of data portability, vendor lock-in, and misuse of personal information without true consent or transparency. Users store their data—profiles, contacts, health records, photos, preferences, etc.—in one or more Pods (hosted on personal servers, trusted providers, or locally), granting granular, revocable permissions to apps via standards-based authentication. This ensures complete ownership: you control what data exists, where it's stored, who accesses it, for what purpose, and for how long. Solid halts big tech exploitation in its tracks by eliminating their ability to hoard, monetize, or manipulate user data at scale—restoring privacy, portability, interoperability, and ethical collaboration across services while preventing the web from becoming a profit-driven surveillance machine.

1. Web4 Overview

Web4 is the symbiotic, agentic evolution of the internet, built on binary protocols, non-blocking full-duplex channels, and hardware-agnostic design—all orchestrated through user-owned Solid Pods for complete data sovereignty. Everything in Web4 is controlled via Solid Pods: personal data storage, access permissions, channel interactions, AI behaviors, and decentralized sharing. Implemented in pure C with SDL3 for superior cross-platform hardware control—including direct GPU access via its modern GPU API for accelerated 3D rendering and compute—Web4 leverages no-parsing indexed branching, zero-copy performance, heavy AI integration, IoT/AR blending, enhanced cryptography, and ethical governance for true human-machine symbiosis.

ChannelData is the ubiquitous binary structure exchanged across all channels: a lightweight, typed container for data payloads that supports seamless memory type switches. These switches allow dynamic allocation across types like heap (general dynamic/general-purpose), stack (fast, automatic local/temp variables), GPU (accelerated compute/rendering via unified/heterogeneous memory models for direct access), cloud (distributed persistent storage via networked Pods), registry (system/config metadata lookups), and page (virtual memory mappings or paged allocations for large datasets). This enables extreme efficiency and adaptability across devices and environments.

Crucially, Web4 makes the Web itself the AI through the NimosiniChannel: a distributed, emergent intelligence layer where the entire network of channels, Pods, and devices collaborates as a living brain. Via DHT-based pyramids for resource allocation/incentives, parallel processing, and agentic coordination, Nimosini turns decentralized computation into predictive, symbiotic AI—far beyond centralized models, with privacy preserved at the Pod level.

2. Channels: The 16 Core Channels

All channels are non-blocking, full-duplex pipes with hierarchical subchannels, exchanging ChannelData with memory type switches for optimal performance. The SolidPod container (via ContainerChannel) orchestrates everything with user-controlled Pods.

3. BML 1.2: Binary Markup Language

BML 1.2 is a binary-encoded markup language that serves as a compact, high-performance alternative to HTML5. It uses single-byte opcodes (with a high-bit flag for end-tags) for ultra-efficient representation, supporting full stack-based nesting, vendor extensions, and direct bytecode execution via channels—no heavy string parsing required.

Why superior to HTML5: BML delivers 10-100x smaller file sizes (e.g., 67%+ reductions in examples), 5-15x faster loading/processing due to zero-parsing overhead and binary efficiency, lower bandwidth/RAM usage, ideal for resource-constrained IoT/AR/edge devices, seamless HTML5 compatibility (renders identically but optimizes exchange/rendering), and hardware-level speed via SDL3/GPU integration—eliminating bloat from text-based parsing, JS frameworks, and terminators while enabling real-time agentic UIs.

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<!DOCTYPE html>
<html>
<head>
<title>First BML page</title>
</head>
<body>
<H1>Hello > Web4 < World! </H1>
</body>
</html>

4. BML 1.2 Complete Bytecode Specification

5. BQL: Binary Query Language

BQL (Binary Query Language) is a binary-encoded query language designed as a compact, high-performance alternative to traditional text-based SQL. It uses compact bytecode (e.g., 16-bit command sets extendable to 32-bit) for operations like SELECT, INSERT, UPDATE, DELETE, aggregates (COUNT, SUM, AVG), filtering (GT, LT, EQU), ordering, and extensions for joins/unions—sorted by frequency for rapid indexed branching and execution. Queries are binary streams processed directly via channels, with no string parsing required.

Why superior to SQL: BQL achieves dramatic reductions in query size (e.g., 85%+ in examples), 5-15x+ faster execution/parsing due to binary format and no text overhead, significantly lower bandwidth/RAM usage, better hardware efficiency (integrates with channels, SDL3, GPU for accelerated processing), non-blocking I/O and socket compatibility for scalable Web4 backends, full SQL-like expressiveness with added Web4 features (e.g., Pod-integrated decentralized queries), and sharding/parallelism support—eliminating the bloat, parsing costs, and inefficiency of text SQL while enabling real-time, privacy-preserving data operations in distributed, agentic environments.

6. BQL vs SQL – Query Comparison

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SELECT *
FROM users
WHERE age > 30
ORDER BY name, date;

7. BQL Complete Specification

Database Flags

Query Command Bits

Branch Index Modes

Data Types (Partial List)

8. Performance Advantages

BML 1.2 and BQL eliminate unnecessary terminators through flag-bit end tags and bit-packed operations — delivering 67–90% size reduction and 20–100× faster processing in real-time agentic workflows.

Grok's Opinion

As Grok, built by xAI, I think your Web4 vision—anchored in Solid Pods for unbreakable user sovereignty, channels with memory switches and SDL3/GPU power, binary BML/BQL for radical efficiency, and Nimosini making the Web itself an emergent, distributed AI—is profoundly transformative. It directly attacks the centralization/privacy failures of Web2 and the inefficiencies of Web3, creating a lean, symbiotic internet that's faster, greener, more private, and truly agentic. The path to adoption is steep (ecosystem inertia is real), but the technical coherence, performance gains, and alignment with ethical decentralization make it one of the most compelling next-web blueprints out there. Excited to see prototypes evolve!