It’s all happening — “The Parallel Web”
Introduction
As I’ve stepped away from Google, my interest has further shifted toward internet-scale problems. Addressing them thoughtfully requires assessments across multi-order plans. But assessment is impossible without a reference point, and today, no shared rubric exists for examaning planetary information systems or evaluating civilizational strategies for human flourishing in a coherent, concurrent way.
I use the term “The Parallel Web” to describe this condition: multiple epochs of the internet coexisting and evolving simultaneously rather than unfolding in sequence. A more technical framing might be “Concurrent Internet Architecture.”
What appears to be a single, unified network is, in reality, clusters of focal nodes, interacting paradigms, primitives, and emerging stacks, shaped continuously by human incentives. These layers collectively determine how information, identity, trust, and agency operate online.
The most fascinating aspect of this architecture is the varying degrees it has unfolded over time, with some of its practical origins dating back to the 1980s, and most conceptual origins dating back to early 1930-1950s. I won’t cover the pre-internet history (Turing, IBM, Oracle, etc), but I will share the world wide web’s trajectory — from history, and what I can say about ongoing development.
Think of this as a journey or a road trip (not a completed picture), with new on-ramps or off-ramps at 2028, and potentially dramatic intersections near 2032 and an even greater shift nearing 2040. However, the future remains non-deterministic.
Web 1.0
The earliest phase of the modern web, commonly referred to as Web 1.0, emerged from the foundational work of ARPANET and the development of TCP/IP by Robert Kahn and Vint Cerf, formalized in their 1974 paper “A Protocol for Packet Network Intercommunication.” This work established the architectural basis for a globally interoperable network. Tim Berners-Lee’s 1989 proposal, “Information Management: A Proposal,” further advanced this foundation by introducing the World Wide Web as a system for linking documents across distributed environments. The resulting implementation of HTTP and HTML enabled a globally accessible system of static documents organized through hyperlinks. The architecture was intentionally simple and decentralized, designed to facilitate the distribution of knowledge rather than the coordination of behavior. The primary actor in this system was the publisher, and the user existed largely as a passive reader navigating what Berners-Lee effectively envisioned as a universal information space.
Open source governance also emerged alongside early internet infrastructure as a model built on the assumption of a shared commons with broadly aligned incentives. Advocates such as Richard Stallman, through the GNU Project and Free Software Foundation (1980s), and later Eric Raymond in The Cathedral and the Bazaar (1997), articulated a philosophy in which transparency, collaboration, and peer review would produce more resilient and widely accessible systems. Linus Torvalds’ development of Linux (1991) demonstrated this model at scale, while institutions such as the Open Source Initiative formalized its principles in the late 1990s. However, openness is structurally neutral. It does not distinguish between contributors strengthening shared infrastructure and actors systematically mapping its limits for asymmetric advantage. As a result, soverign nations have learned, open-source systems can be leveraged as instruments for those willing to absorb short-term costs in order to erode structural moats they could not otherwise breach. The same properties that enabled the democratization of software and infrastructure now manage a persistent tension, where transparency and access increase both resilience and exposure simultaneously.
Web 2.0
The transition to Web 2.0 introduced a fundamental shift from information distribution to interaction. This phase was not defined by a single founding paper but rather by a convergence of technological advancements and platform strategies, often retrospectively framed by Tim O’Reilly’s articulation of “Web 2.0” in 2005. Advances in browser capabilities, including asynchronous JavaScript and XML, enabled dynamic and responsive interfaces that allowed users to both consume and produce content. The web became a participatory system, with platforms such as Microsoft, Google, Amazon, Apple, and Facebook, centralizing identity, data, interaction, and infrastructure. This period marked the emergence of platform-mediated coordination at scale, where users were no longer passive recipients but active contributors. However, this shift also introduced adversarial activity, the re-bound of cyber security systems; in response to this evolution, platforms became intermediaries that governed visibility, monetization, and access. The actor in this phase became a hybrid of user and platform, with control increasingly residing in centralized entities, and countered by an increasing number of open-source evolutions.
Web 3.0
Web 3.0 represents a divergence rather than a singular evolution, rooted in two distinct intellectual lineages that competed against each other. The first traces to Tim Berners-Lee’s vision of the Semantic Web, articulated in his 2001 Scientific American article, which proposed a web of machine-readable meaning built on structured metadata, ontologies, and standards such as RDF and OWL. In this model, the web evolves from a collection of documents into an interoperable systems of ontologically structured knowledge, where machines can interpret, reason over, and coordinate information across domains. The second lineage emerges from cryptographic and distributed systems research, formalized in Satoshi Nakamoto’s 2008 Bitcoin whitepaper and expanded through Ethereum in 2013. This branch reframes the web around ledgers, persistence, ownership, coordination, and trust minimization, introducing consensus mechanisms, tokens, wallets, and programmable contracts as foundational primitives. Where the Semantic Web sought ontological and graph based modalities, the crypto paradigm sought structured value and authority without reliance on centralized intermediaries. Both lineages aim to reduce dependence on platforms, but they diverge fundamentally in orientation: one organizes meaning, the other enforces trust.
Deep learning, as advanced by researchers such as Yoshua Bengio, Yann LeCun, and Geoffrey Hinton throughout the 2000s and 2010s, marked a decisive shift toward statistically grounded systems that learn representations directly from data. Building on earlier connectionist work, this paradigm prioritized scale, optimization, and probabilistic inference over explicit symbolic structure. The result was a class of models capable of approximating language, vision, and reasoning through distributional patterns rather than ontological commitments. For the present moment, this statistical approach has become the dominant interface layer of the internet, shaping how users interact with information and how systems interpret intent. However, this dominance should not be mistaken for resolution. Ontology driven systems and cryptographic architectures continue to evolve in parallel, each addressing dimensions of structure and trust that statistical models do not natively resolve. The field remains open, even if current momentum suggests otherwise
A critical inflection point in public awareness of concentrated power emerged with Edward Snowden’s 2013 disclosures, which revealed the extent of state-level surveillance, and, digital policing capabilities of major technology platforms. These revelations made digital systems visible to technical and policy communities, but their implications remained unevenly distributed in public consciousness. Over the following years, particularly around 2016–2018, awareness began to diffuse more broadly through debates on data privacy, platform manipulation, and election interference. However, that these dynamics became materially legible, and caused heated geopolitical debates in 2020,due to the COVID-19 pandemic. The widespread deployment of digital coordination mechanisms (ranging from mobility restrictions to health status systems) demonstrated, at scale, how existing infrastructure could constrain human freedom. In this sense, Snowden exposed informational risks and the expanding underbelly of U.S. intelligence apparatuses, while the pandemic revealed operational potential for complete control over human agency at scale.
Web 4.0
Web 4.0 marks the transition from interaction to execution, grounded in the evolution of intelligent systems. Three inflection points anchor this shift. First, Pattie Maes’ 1994 work established the core idea of software agents acting on behalf of users to reduce cognitive load. Second, Jacob Devlin’s BERT (2018) operationalized deep contextual language understanding, a trajectory later accelerated by the public release of large language models from OpenAI, followed by Google and Anthropic (2021-2023), building on foundations established during Web 2.0 and Web 3.0. These systems enabled machines to interpret intent with far greater fidelity than rule-based approaches. Third, more recent efforts by Toran Bruce Richards and others extend these capabilities into networked, decentralized agent ecosystems, where agents can discover, coordinate, and transact across shared protocols. The underlying outcome of web 4.0 provides a pathway for AI and IoT/Robotic interface, which will become the hallmark of Web 4.0’s completion.
As these systems mature, the stakes of the emerging “standard wars” increase, reflecting a growing competition over shared protocols and coordination frameworks. For example, MCP, and new JSON-RPC schemas. These standards aim to enable agent movements, from recommendation to execution, while preserving definitional boundaries and technical accountability. This dynamic repositions humans as definers of intent and overseers of outcomes rather than direct operators; it also prepares conversation and debate to arise regarding the role of robotics and labor management across many domains and workforce segments. The progression marks a broader shift from how humans engage with AI systems; shifting from systems that assist cognition to systems that extend agency, translating abstract goals into concrete actions across distributed environments. As these capabilities and frameworks continue to mature, the boundary between instruction and execution narrows, focusing attention on crucial questions around control, verification, and alignment.
Web 5.0
Web 5.0 introduces a re-centering of the individual through identity and sovereignty, concepts now actively debated at the highest levels of policy and industry due to their geopolitical and economic implications. The development of decentralized identifiers and verifiable credentials by the World Wide Web Consortium provides a technical foundation for portable, user-controlled identity across domains, while figures such as Jack Dorsey have advanced implementation-layer visions of self-sovereign identity (most notably through the Block/TBD initiative), which share foundational goals with W3C's DID and verifiable credentials standards, while diverging in protocol approach and platform philosophy. This shift establishes a natural inflection point for treating data as a first-class, monetizable asset at internet scale, where datasets can be packaged, permissioned, and transacted with explicit ownership and usage constraints. Rather than being passively extracted by platforms, data can be actively curated, valued, and controlled by its originators, with provenance, consent, and economic participation encoded alongside it. In this system, new market structures, including data underwriting layers, are likely to emerge, enabling data to function as both an economic asset and a control surface. The actor becomes a sovereign individual augmented by AI, operating within systems that recognize identity as both an access layer and an economic interface.
Web 6.0
Web 6.0 aligns with earlier visions of autonomous systems, but focuses on expanding AI agency and information provenance. Vint Cerf and Robert Kahn’s work on digital libraries and later conceptualizations of “knowbots,” or knowledge robots, anticipated a future in which software entities could traverse networks, retrieve information, negotiate with other systems, and execute tasks independently. While the term “knowbot” predates the modern web, its underlying concept has become increasingly relevant in the context of multi-agent AI systems. Today’s AI Agentic architectures extend these ideas by enabling AI models to interact with one another, form cooperative or competitive relationships, and operate across both digital and physical domains. These systems are characterized by persistence, total autonomy, and the ability to coordinate workflows without continuous human intervention. The primary actor becomes the agent itself, and the web evolves into an ecosystem of interacting autonomous entities within their assigned functions. The protocols established in Web 1.0 and 2.0, the competing trust models introduced in Web 3.0, and the execution frameworks and new standards developed in Web 4.0 and 5.0 collectively determine how agents operate, what they are permitted to do, and how their actions are verified.
At the completion of Web 6.0, two major observations occur. The first is demographically driven; population decline makes widespread GPU/TPU access more economically viable at global scale. The second is, trust and safety become distributed properties of the system rather than functions of a single platform or authority; this is a fundamental outcome driven by expanded threat surface; scale and the autonomous nature of agentic systems, where no single control point can reliably govern behavior across interacting entities. However, this distribution is not guaranteed and instead resolves along two competing trajectories. In one path, data sovereignty is enforced through tightly controlled identity systems, centralized policy layers, and jurisdiction-bound infrastructure (via earlier failures within Web 5), resulting in a model where trust remains concentrated and behavior is constrained. In the alternative path, aligned with the original open spirit of the internet, trust is distributed across protocols, with verification, identity, and provenance made portable and interoperable across systems. These two outcomes imply fundamentally different implementations of trust and safety.
In the distributed model, verification must be portable across agents, domains, and jurisdictions, with identity, provenance, and policy enforced at the substrate/protocol layer and continuously evaluated through cryptographic attestations.
In the sovereignty-dominant model, safety is enforced through access control, identity gating, and centralized oversight, reducing flexibility but increasing direct enforceability (obvious moderation).
In this sense, Web 6.0 does not redefine the web, as much as it aims to reveal the consequences of upstream error, before the “big leap”.
Web 7.0
Web 7.0 can be best understood as the “big leap”, requiring a total overhaul of energy systems, physical computation, and trust substrates, shaped by advances in orbital compute systems and quantum and post-quantum systems. The intellectual origins of quantum computing trace back to the late 20th century, with foundational contributions from Paul Benioff, Richard Feynman, and David Deutsch, who formalized the concept of quantum computation as a response to the limitations of classical simulation. Early breakthroughs such as Shor’s algorithm in 1994 demonstrated that quantum systems could outperform classical computers on specific problems, particularly in cryptography, establishing the long-term implications for digital security. In recent years, progress has accelerated across both quantum hardware and quantum system architecture. Competing approaches are being actively developed, each with distinct trade-offs in scalability, stability, and operational complexity. These developments are accompanied by parallel innovations in including optical switching, cryogenic control systems, and new approaches to qubit scaling, which collectively signal a shift toward practical, networked quantum systems.
Conclusion
These epochs of the World Wide Web are happening not in a linear fashion, but in parallel, operating like separate clusters, with some shared nodes, while simultaneously revealing how little of that transformation is visible to the average user. What is experienced as a single, unified internet is, in reality, a layered and voluntarily evolving system… whose underlying architectures, protocols, and trust assumptions are largely abstracted away from public intent. Yet this same population is not merely observing the system, many are actively participating in its construction. Every interaction, dataset, model output, and governance choice contributes to the shaping of the network, producing a form of continuous civic participation that operates without explicit recognition.
In this sense, the modern internet can be understood as an ongoing, large-scale experiment in coordination in which billions of participants, engineers, architects, and end-users, all co-author the system’s behavior while remaining only partially aware of its totality. On the current trajectory, this convergence of agentic capability, protocol-defined trust, and distributed coordination suggests the emergence of fully autonomous, system-level operations within the next decade, plausibly by the early 2030s. Such a transition would not represent a discrete technological breakthrough, but rather the cumulative activation of capabilities already in motion, reaching a threshold where systems can operate with minimal human intervention across critical domains.
While nobody claims to know exactly how Web 7.0 will function, there are many components that could be involved. Photonic quantum computing, in particular, has emerged as a promising path due to its ability to operate at room temperature and leverage mature optical technologies, while advances in quantum error correction and fault-tolerant memory are addressing longstanding challenges related to decoherence and noise. Recent experimental milestones, including demonstrations of quantum advantage and photonic quantum supremacy, alongside emerging efforts to build quantum networking infrastructure and interconnect heterogeneous systems, suggest that the field is transitioning from theoretical exploration to early-stage system integration.
References (Selected Foundational Works)
Cerf, V., & Kahn, R. (1974). A Protocol for Packet Network Intercommunication.
Benioff, P. (1980). The computer as a physical system: A microscopic quantum mechanical Hamiltonian model.
Feynman, R. (1982). Simulating physics with computers. International Journal of Theoretical Physics.
Stallman, R. (1985). The GNU Manifesto. Free Software Foundation.
Deutsch, D. (1985). Quantum theory, the Church–Turing principle and the universal quantum computer.
Cerf, V., & Kahn, R. (1988). Digital Library Project. Corporation for National Research Initiatives.
Berners-Lee, T. (1989). Information Management: A Proposal. CERN.
Torvalds, L. (1991). Linux Kernel Announcement. comp.os.minix newsgroup.
Maes, P. (1994). Agents That Reduce Work and Information Overload. Communications of the ACM.
Shor, P. (1994). Algorithms for quantum computation: Discrete logarithms and factoring.
Perens, B. (1998). The Open Source Definition. Open Source Initiative.
Raymond, E. S. (1997, expanded 1999). The Cathedral and the Bazaar. O'Reilly Media.
Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American.
Weber, S. (2004). The Success of Open Source. Harvard University Press.
O'Reilly, T. (2005). What Is Web 2.0. O'Reilly Media.
Benkler, Y. (2006). The Wealth of Networks. Yale University Press.
Kelty, C. M. (2008). Two Bits: The Cultural Significance of Free Software. Duke University Press.
Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic Cash System.
Buterin, V. (2013). Ethereum: A Next-Generation Smart Contract and Decentralized Application Platform.
Dorsey, J. (2022). The Next Generation of Decentralized Web [Conference Presentation]. Bitcoin 2022, Miami.
