Agentic Web: Weaving the Next Web with AI Agents

Chenyu Gong; Costas Spanos; Dawn Song; Haoran Geng; Huacan Chai; Jun Wang; Meng Fang; Ming Jin; Muhao Chen; Mulei Ma

REVIEW 3 major objections 5 minor 6 cited by

Agentic Web: Weaving the Next Web with AI Agents

T0 review · 3 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

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Pith's one-line read This paper defines the Agentic Web as an internet era in which autonomous AI agents — not humans — become the web's primary actors, planning, negotiating, and transacting across services on behalf of users.

desk verdict A solid, useful survey of the agentic-web landscape with a coherent three-dimensional frame, but with a real internal tension between its 'essential condition' of standardized interfaces and its own GUI-automation applications; conditional acceptance is the right call. read the letter →

arxiv 2507.21206 v1 pith:KQZ4OQDT submitted 2025-07-28 cs.AI cs.LG

Yingxuan Yang , Mulei Ma , Yuxuan Huang , Huacan Chai , Chenyu Gong , Haoran Geng , Yuanjian Zhou , Ying Wen

show 10 more authors

Meng Fang Muhao Chen Shangding Gu Ming Jin Costas Spanos Yang Yang Pieter Abbeel Dawn Song Weinan Zhang Jun Wang

This is my paper · ORCID

classification cs.AIcs.LG

keywords AgenticWebLLMagentsarchitectureagentcommunicationprotocolsModelContextProtocol(MCP)Agent-to-Agent(A2A)attentioneconomymulti-agentcoordination

verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

The paper argues that the internet is entering a third era — the Agentic Web — in which autonomous, LLM-powered agents, not humans, become the web's primary actors. It formally defines this era as a distributed ecosystem where agents persistently plan, coordinate, and execute goal-directed tasks on behalf of users, and it claims this is a structural shift, not an incremental one: the web turns from a network of linked documents into a network of interacting agents, and value flows directly between agents rather than only through human attention. The framework rests on three core conditions — agent autonomy, standardized machine-readable interfaces, and agent-to-agent value exchange — and a three-dimensional model of intelligence, interaction, and economics. A sympathetic reader would care because the paper gives a coherent, testable vocabulary for a transition that commerce, search, and infrastructure would all have to reorganize around if it is real.

What carries the argument

The carrying structure is the formal definition together with the three Core Conditions of Section 3.1: agents must act as autonomous intermediaries; web resources must be accessible through standardized, machine-readable interfaces; and value must be exchanged directly between agents. Around these, the paper builds a three-dimensional conceptual model — Intelligence (perception, planning, learning), Interaction (semantic protocols and tool orchestration), and Economics (machine-native value creation) — and a proposed Client-Agent-Server architecture that replaces the traditional Client-Server model. The operative mechanisms are the two emerging protocols: MCP (Model Context Protocol), which standardizes how agents connect to tools and resources, and A2A (Agent-to-Agent), which lets agents discover one another, maintain task state, and collaborate asynchronously. These protocols and conditions are what would turn the definition from a metaphor into an infrastructure.

What would settle it

Monitor the deployment of standardized agent-native interfaces across the largest web services over the next several years. If the dominant mode of agent-web interaction remains GUI automation, DOM scraping, and provider-specific APIs, with no measurable competition among services for agent invocation such as agent-targeted advertising or invocation-based pricing, then the paper's central structural shift has not occurred, and the Agentic Web remains a description of platform assistants rather than a new web architecture.

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Extended reading notes

Core claim

The paper's central claim is its formal definition: "The Agentic Web is a distributed, interactive internet ecosystem in which autonomous software agents, often powered by large language models, act as autonomous intermediaries that persistently plan, coordinate, and execute goal-directed tasks." The authors contend that this marks the third phase of the web, after the PC Web (search and static pages) and the Mobile Web (recommendation and the attention economy). In this phase, humans remain the end users, but AI agents become the mid users: they are the entities that navigate, compare, book, negotiate, and produce content, often consuming content generated by other agents. The paper argues that every foundational web concept must be reinterpreted — hyperlinks become coordination channels, webpages become agents, PageRank-style authority gives way to cooperation-based agent rankings, and search engines become orchestrators that compose and manage workflows. Commercially, the web shifts from an attention economy to an "Agent Attention Economy" in which services compete to be selected and invoked by agents.

Load-bearing premise

The load-bearing premise is Core Condition 2: that web resources will actually become accessible through standardized, machine-readable interfaces at scale; if providers keep offering plain HTML, ad-hoc APIs, or GUI-only access, agents will keep scraping and clicking, and the Client-Agent-Server architecture and Agent Attention Economy the paper derives will not take shape.

Editorial extensions

If this is right

Search and discovery transform: search engines become orchestration layers that recruit, compose, and manage agents, and page authority is replaced by cooperation success, responsiveness, and contribution to multi-agent workflows.
The commercial model shifts: services, tools, and other agents compete for agent invocation rather than human clicks, giving rise to agent-targeted advertising, capability reranking, and auction-based ranking in service registries.
Web infrastructure must migrate to a Client-Agent-Server architecture with task-level service guarantees (the Service Requirement Zone), persistent context, and asynchronous, event-driven agent communication beyond HTTP/RPC.
Content production becomes agent-native: agents generate tools, manifests, summaries, and structured artifacts for other agents, creating self-sustaining loops of machine-produced and machine-consumed knowledge.
Security and governance move from isolated incident response to cascade prevention: cross-layer threat chains (cognitive to protocol to economic) and autonomous financial authority require zero-trust architectures, reasoning guardrails, and new liability frameworks.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

The paper does not propose a direct empirical test of its own transition claim; a natural one is to track the share of major web services that expose standardized agent endpoints (MCP/A2A) rather than remaining reachable only through scraping or GUI automation, since the framework predicts the former must grow for the Agentic Web to be more than a platform feature.
Extending the Agent Attention Economy logic, the metrics that currently price digital advertising — click-through rate, dwell time, cost per mille — would lose their predictive link to revenue once the scarce resource becomes agent selection rather than human attention; the paper gestures at this displacement but does not quantify it.
The framework implicitly calls for a research program the paper leaves open: designing agent-authority and trust metrics analogous to PageRank, validated on multi-agent task-completion records, and building billing ledgers that trace a single user command through chains of sub-agents.
A governance consequence the paper leaves implicit: liability for an autonomous agent's completed actions, rather than technical capability, is likely to be the binding constraint on deployment speed in the transactional domain, because the economic dimension presupposes that agents can commit real resources.

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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Desk Editor's Note

read the letter

This is a survey and position paper, not an empirical result, and it should be judged that way. The useful core is the organizing frame: three dimensions (intelligence, interaction, economics) plus a historical narrative that moves from search to recommendation to agentic action. The protocol summaries for MCP and A2A are accurate and clearly explained, the taxonomy of Agent-as-Interface, Agent-as-User, and Agent-with-Physics is genuinely helpful, and the risk section is more detailed and credible than most work in this area. There is no code or data to check, but for this genre the value is organizational, and the paper does that job well.

The main soft spot is real. Section 3.1 lists "web resources need to be accessible through standardized, machine-readable interfaces" as an essential condition of the Agentic Web, yet Section 6.2.2 and Table 3 classify Anthropic Computer Use and Google Project Mariner—systems that operate through vision-based GUI manipulation and simulated clicks—as current applications. That is a direct contradiction: either GUI automation counts as part of the paradigm, in which case Condition 2 is not necessary, or it does not count, and the paper's own application taxonomy is incoherent. The stress-test note is correct on this. It is not a fatal flaw for the survey as a whole, but the authors need to reframe Condition 2 as a design goal for a mature phase, or explicitly explain why GUI-based agents are partial precursors that satisfy the spirit rather than the letter.

A related overstatement appears in Section 5.2.1, where the traditional Client-Server architecture is called "fundamentally invalidated." The proposed Client-Agent-Server model and MCP/A2A protocols are themselves layered on HTTP and JSON-RPC, so the honest claim is that the old model is insufficient, not invalidated. The invented roadmap components in Figure 10 (DSVM, RTR, CABL) are fine as illustrative architecture, but they should be labeled more clearly as speculative rather than implemented.

Citation patterns look reasonable, including the self-citations; they are not load-bearing. Novelty is modest—this is a synthesis of existing ideas with a new packaging—but the packaging is coherent and the coverage is broad enough to be useful to people entering the area.

Who is this for? Researchers and engineers who want a map of agent protocols, application categories, and security risks, and who need a shared vocabulary for discussing agent-driven web infrastructure. It deserves a serious referee, not a desk reject. My recommendation: conditional accept, with the Core Condition 2 tension and the "fundamentally invalidated" language flagged as required revisions.

Referee Report

3 major / 5 minor

Summary. The manuscript is a position/survey paper that proposes the 'Agentic Web' as a new phase of the internet in which LLM-powered agents act as autonomous intermediaries for users. Section 3 defines the Agentic Web and lists three 'Core Conditions': agent autonomy, standardized machine-readable interfaces, and agent-to-agent value exchange. The authors organize the paradigm into intelligence, interaction, and economic dimensions; trace algorithmic transitions from retrieval to planning and from single-agent to multi-agent coordination; propose a Client-Agent-Server system architecture built around MCP and A2A protocols; survey current applications (Agent-as-Interface, Agent-as-User, Agent-with-Physics); and discuss risks, red-teaming, defenses, and open problems. The paper makes no quantitative or formal claims; its contribution is conceptual framing and synthesis of existing work.

Significance. Conditional on its internal consistency being repaired, the paper could serve as a useful organizing survey for the agentic-web research agenda. Its strengths are the accessible historical narrative (Section 2), the protocol descriptions of MCP and A2A (Sections 5.3.2 and 5.3.3), and the threat taxonomy in Tables 5 to 7. The risk discussion is credible and cites concrete exploits and existing frameworks. However, the paper's central architectural claim rests on a load-bearing premise, that standardized machine-readable interfaces are an 'essential' condition, that is contradicted by its own application taxonomy, and several named system components (DSVM, RTR, CABL) are placeholders. The paper is explicitly speculative about the Agent Attention Economy in Section 2.3.2 and explicitly acknowledges the lack of quantitative cascade-risk models in Section 7.1.2. Thus, as it stands, the contribution is a plausible taxonomy rather than a validated framework.

major comments (3)

[§3.1 (Core Condition 2) vs. §6.2.2 and Table 3] Core Condition (2) states that 'Web resources need to be accessible through standardized, machine-readable interfaces' and the surrounding text calls these conditions 'essential.' Yet §6.2.2 classifies Anthropic Computer Use, Google Project Mariner, and ChatGPT Agent as current Agentic Web applications even though these systems operate through vision-based GUI manipulation, DOM parsing, and simulated clicks, none of which require standardized machine-readable interfaces. The paper even contrasts API-based (Agent-as-Interface) with GUI-level (Agent-as-User) automation in §6.2.2, and §2.3.1 criticizes 'DOM scraping or simulated clicks' as 'outdated and brittle' while still counting such systems as part of the paradigm. This is a self-contradiction at the core of the paper's definitional claim. Either Core Condition (2) must be weakened to a design pathway rather than a necessary condition, or the Agent-as-User systems in §6.2.2 must be explicitly excluded from the Agentic Web; the current text cannot have both.
[§5.2.1 (Roadmap of the Agentic Web System) and Figure 10] The text states that 'These rigorous requirements fundamentally invalidate the traditional Client-Server architecture, mandating a shift toward the Client-Agent-Server model.' This overstatement is not supported by the paper's own protocol discussion: MCP is a client-server protocol layered on JSON-RPC and HTTP, and A2A agent cards and messages are JSON documents exchanged over HTTP, as described in §5.3.2 and §5.3.3. The proposed architecture extends client-server interaction with an agent intermediary; it does not invalidate it. Moreover, the three components introduced in Figure 10, namely the Demand-Skill Vector Mapper (DSVM), the Real-Time Task Router (RTR), and the Cross-Agent Billing Ledger (CABL), are named and given one-sentence descriptions but no interface definitions, algorithms, or evidence; as presented, they are not a 'roadmap' but placeholders.
[§5.3.1 (Design Motivation: Beyond HTTP/RPC)] The paper claims that HTTP and RPC are 'inadequate' for the Agentic Web because they lack semantic-level support, semantic accuracy, and interactivity. However, MCP and A2A, the two protocols offered as successors, run over HTTP and JSON-RPC. The correct claim appears to be that a semantic layer on top of existing transports is needed, not that HTTP/RPC are wholly replaced. The paper should explicitly state whether it is arguing for replacement or augmentation. As written, the 'Beyond HTTP/RPC' framing and the later 'fundamentally invalidate' statement in §5.2.1 give readers contradictory pictures of the relationship between current protocols and the proposed agentic infrastructure.

minor comments (5)

[§5.2.2] The phrase 'yool orchestrator agent' appears to be a typo for 'tool orchestrator agent'.
[§7.3.1] The word 'dialogus' should be 'dialogue' or 'dialogues.'
[§2.3.2] The Agent Attention Economy is repeatedly presented as an emerging fact, but the section itself supports it only with 'it is reasonable to hypothesise.' Please mark it consistently as a conjecture and, if available, cite empirical evidence or at least market data rather than only analogous reasoning.
[Throughout] The manuscript uses 'Agentic Web' and 'AgentWeb'/'Agent Web' inconsistently; for example, §5.3.3 refers to an 'Agent Web system.' Please unify the terminology.
[§5.3.1] The statement that 'a large number of new agent communication protocols emerged' cites only Yang et al. 2025d; an independent survey or registry reference would make this claim easier to verify.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the Agentic Web is a definitional position/survey, not a derivation; self-citations are contextual and the central claim rests on external examples and benchmarks.

full rationale

The paper makes no fitted prediction and contains no equation or reduction that equates an output to its input. Its central move is definitional: Section 3 defines the Agentic Web and states three core conditions, then organizes existing work (MCP, A2A, ChatGPT Agent, Anthropic Computer Use, Project Mariner, Genspark, WebArena, OSWorld, etc.) under that definition. Because the contribution is a framework and taxonomy rather than a derived theorem, there is no derivation chain whose conclusion is presupposed. The self-citations that do appear (e.g., Yang et al. 2025d for agent communication protocols, Yang et al. 2025f for the Agent Attention Economy, Yang et al. 2023b for the Service Requirement Zone) support background claims or name concepts introduced in the same research program, but the load-bearing assertions - that LLM agents can autonomously plan and execute tasks, that agent protocols such as MCP and A2A exist and are being adopted, and that web agents are being deployed commercially - are documented with external sources and public products. The internal tension between Core Condition 2 (standardized, machine-readable interfaces) and the Agent-as-User systems that operate through GUI and vision-based automation is a genuine inconsistency in the framework, but it is not a circular step: the paper does not define GUI automation in terms of the Agentic Web and then use the Agentic Web to explain GUI automation. No fitted parameter is renamed as a prediction, no uniqueness theorem is imported from the authors, and no ansatz is smuggled in by citation. Accordingly, the appropriate finding is no significant circularity, with a low score reflecting only the presence of minor, non-load-bearing self-citations and the definitional character of the central concept.

Assumptions & free parameters 0 free parameters · 4 assumptions · 5 invented entities

The paper's central claims rest on the feasibility and adoption of standardized agent communication and on LLM agents continuing to improve; these are assumed rather than established. The paper also introduces several named system components as proposals; none is implemented or independently verified.

assumptions (4)

domain assumption LLM-based agents will continue to gain in capability, reliability, and user trust, enabling widespread delegation of multi-step tasks.
The paper's entire framing depends on this trajectory; asserted in Section 1 and Section 2.3.1, but not evidenced within the paper.
domain assumption Web resources and services will become accessible through standardized, machine-readable interfaces (e.g., MCP, A2A, or similar), at scale and with sufficient semantic clarity.
Core Condition 2 in Section 3.1; the architecture in Section 5.2.1 presumes this standardization.
domain assumption Value will be exchanged directly between agents through billing ledgers and micropayment frameworks, making the 'Agent Attention Economy' viable.
Section 3.3.3 and Section 5.2.1 introduce the Cross-Agent Billing Ledger as a component without evidence of technical or regulatory feasibility.
ad hoc to paper The three-dimensional decomposition (intelligence, interaction, economics) is a meaningful and useful categorization for understanding the agentic web.
Section 3.3 introduces this framework as a conceptual contribution; it is a modeling choice, not a discovered structure.

invented entities (5)

Agent Attention Economy
purpose: Hypothesized economic pattern where services compete for agent invocation rather than human clicks.
Introduced in Section 2.3.2 and used to predict future monetization models; no empirical evidence or formal model grounds it.
Service Requirement Zone (SRZ)
purpose: Eight-dimensional profile of quality-of-experience needs for agentic tasks, used to motivate network orchestration.
Presented in Section 5.1 (Figure 9) as a conceptual tool; no validation or measurement of real agent tasks is provided.
Demand-Skill Vector Mapper (DSVM)
purpose: Component of the proposed Agentic Web Architecture that maps service demands to machine-readable vectors.
Proposed in Section 5.2.1 (Figure 10) as part of a roadmap; not implemented.
Real-Time Task Router (RTR)
purpose: Component that dispatches vectorized tasks to a distributed agent framework.
Proposed in Section 5.2.1; no implementation or evaluation.
Cross-Agent Billing Ledger (CABL)
purpose: Ledger for metering and settling economic interactions between agents.
Proposed in Section 5.2.1 as a design element; no prototype or feasibility analysis.

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Cite this review

Pith. "Pith review of Agentic Web: Weaving the Next Web with AI Agents." pith.science (2026). https://pith.science/paper/KQZ4OQDT

@misc{pith2026250721206,
  author       = {Pith},
  title        = {Pith review of: Agentic Web: Weaving the Next Web with AI Agents},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KQZ4OQDT}},
  note         = {Machine review of arXiv:2507.21206}
}

read the original abstract

The emergence of AI agents powered by large language models (LLMs) marks a pivotal shift toward the Agentic Web, a new phase of the internet defined by autonomous, goal-driven interactions. In this paradigm, agents interact directly with one another to plan, coordinate, and execute complex tasks on behalf of users. This transition from human-driven to machine-to-machine interaction allows intent to be delegated, relieving users from routine digital operations and enabling a more interactive, automated web experience. In this paper, we present a structured framework for understanding and building the Agentic Web. We trace its evolution from the PC and Mobile Web eras and identify the core technological foundations that support this shift. Central to our framework is a conceptual model consisting of three key dimensions: intelligence, interaction, and economics. These dimensions collectively enable the capabilities of AI agents, such as retrieval, recommendation, planning, and collaboration. We analyze the architectural and infrastructural challenges involved in creating scalable agentic systems, including communication protocols, orchestration strategies, and emerging paradigms such as the Agent Attention Economy. We conclude by discussing the potential applications, societal risks, and governance issues posed by agentic systems, and outline research directions for developing open, secure, and intelligent ecosystems shaped by both human intent and autonomous agent behavior. A continuously updated collection of relevant studies for agentic web is available at: https://github.com/SafeRL-Lab/agentic-web.

Figures

Figures reproduced from arXiv: 2507.21206 by the authors.

**Figure 2.** Evolution of user-system interaction across three internet eras. In the PC Web Era, users [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗

**Figure 3.** Timeline of Web Evolution. The three eras of web evolution are not strictly distinct. Their [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗

Figures from the paper (10 more)

**Figure 4.** Figure 4: Attention Flow Evolution Across Web Eras. This diagram illustrates the transition from [PITH_FULL_IMAGE:figures/full_fig_p010_4.png]

**Figure 5.** Figure 5: Agent Workflow under the Agentic Web. In the following sections, we examine the rise of this agent-based infrastructure and its profound implications on Web architecture and digital economics. 2.3.1 Rise of Agentic Web In the Agentic Web Era, tasks that once required s…

**Figure 6.** Figure 6: Conceptual Framework of the Agentic Web. This diagram illustrates a three-dimensional [PITH_FULL_IMAGE:figures/full_fig_p016_6.png]

**Figure 7.** Figure 7: Architectural evolution of Web System. The transition reflects a shift from static content [PITH_FULL_IMAGE:figures/full_fig_p020_7.png]

**Figure 8.** Figure 8: Algorithmic Transitions for the Agentic Web. The figure illustrates three foundational [PITH_FULL_IMAGE:figures/full_fig_p021_8.png]

**Figure 9.** Figure 9: Service Requirement Zone. ascertain the underlying intent or operational semantics of the API’s methods. To transcend this limitation, a new paradigm of agent-oriented APIs is required. A future standard would likely necessitate the integration of machine-readable for…

**Figure 10.** Figure 10: Agentic Web Roadmap multimodal systems that integrate diverse inputs such as voice and gesture, embodied in devices like smart speakers and wearable technology. The Intelligent Agent constitutes the system’s central cognitive and decision-making nexus. Leveraging art…

**Figure 11.** Figure 11: Interaction Process Example: Planning a Travel Itinerary [PITH_FULL_IMAGE:figures/full_fig_p028_11.png]

**Figure 12.** Figure 12: The above schematic illustrates a rudimentary AgentWeb system, with A2A and MCP [PITH_FULL_IMAGE:figures/full_fig_p032_12.png]

**Figure 13.** Figure 13: Illustration of the Agentic Web Safety and Security Ecosystem. The central hexagon [PITH_FULL_IMAGE:figures/full_fig_p042_13.png]

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 6 Pith papers

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LocalSearchBench—1.3M merchant records and 900 multi-hop local-life QA tasks across 9 Chinese cities—shows the best reasoning agent reaches only 35.6% correctness.
Throttling Web Agents Using Reasoning Gates
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cs.AI 2025-09 conditional novelty 5.0 of 10

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cs.MA 2025-08 unverdicted novelty 4.0 of 10

BetaWeb promises a blockchain-enabled trustworthy agentic web, but the submitted manuscript body is a different mining-robot paper, leaving the proposal without supporting evidence.

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" write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 gl...

Pith tools

Reviewed August 6, 2026 · model on record in the stance chip above.

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