Agentic Web
Free while signed in. Answers cite the passages they came from.
This paper introduces the concept of the Agentic Web, a transformative vision of the internet where autonomous AI agents, powered by LLMs, act on behalf of users to plan, coordinate, and execute tasks. It proposes a structured framework for understanding this shift, situating it as a successor to the PC and Mobile Web eras. The Agentic Web is defined by a triplet of core dimensions, intelligence, interaction, and economics, and involves fundamental architectural and commercial transitions.
From static browsing to agentic delegation: The Web transitions from human-led navigation (PC era) and feed-based content discovery (Mobile era) to agent-driven action execution. Here, users delegate intents like “plan a trip” or “summarize recent research,” and agents autonomously orchestrate multi-step workflows across services and platforms.
Three dimensions of the Agentic Web: Intelligence: Agents must support contextual understanding, planning, tool use, and self-monitoring across modalities. Interaction: Agents communicate via semantic protocols (e.g., MCP, A2A), enabling persistent, asynchronous coordination with tools and other agents. Economics: Autonomous agents form new machine-native economies, shifting focus from human attention to agent invocation and task completion.
Algorithmic transitions: Traditional paradigms like keyword search, recommender systems, and single-agent MDPs are replaced by agentic retrieval, goal-driven planning, and multi-agent orchestration. This includes systems like ReAct, WebAgent, and AutoGen, which blend LLM reasoning with external tool invocation, memory, and planning modules.
Protocols and infrastructure: To enable agent-agent and agent-tool communication, the paper details protocols like MCP (Model Context Protocol) and A2A (Agent-to-Agent), along with system components such as semantic registries, task routers, and billing ledgers. These redefine APIs as semantically rich, discoverable services.
Applications and use cases: From transactional automation (e.g., booking, purchasing), to deep research and inter-agent collaboration, the Agentic Web supports persistent agent-driven workflows. Early implementations include ChatGPT Agent, Anthropic Computer Use, Opera Neon, and Genspark Super Agent.
Risks and governance: The shift to autonomous agents introduces new safety threats, such as goal drift, context poisoning, and coordinated market manipulation. The paper proposes multi-layered defenses including red teaming (human and automated), agentic guardrails, and secure protocols, while highlighting gaps in evaluation (e.g., lack of robust benchmarks for agent safety).
Intelligence: Agents must support contextual understanding, planning, tool use, and self-monitoring across modalities.
Interaction: Agents communicate via semantic protocols (e.g., MCP, A2A), enabling persistent, asynchronous coordination with tools and other agents.
Economics: Autonomous agents form new machine-native economies, shifting focus from human attention to agent invocation and task completion.
Get next week’s papers.
The same picks and the same summaries, in your inbox. Free, and 176 issues deep.
Subscribe on Substack