Not long ago large-language-model (LLM) agents were little more than whimsical chat-bots. In 2025 they write production code, manage data pipelines, fly quad-copters and trade electricity on smart grids. What still feels primitive is how these specialists find one another, divide labour and settle the bill. Today most agents live inside isolated sandboxes, speak home-grown dialects and coordinate through brittle, hard-coded playbooks.
The Internet of Agents (IoA) is emerging as a response. The idea is simple but radical: give software entities the same first-class, routable presence that humans and devices enjoy on the Web, then add a “TCP/IP of intent” so that discovery, messaging, trust and payments become native capabilities rather than bespoke hacks. Academic prototypes such as the original IoA framework already demonstrate that dozens of heterogeneous agents can self-assemble into ad-hoc teams and outperform monolithic baselines on complex reasoning tasks.

Why Classical Architectures Fail at Multi-Agent Scale

Three structural bottlenecks keep current LLM frameworks from scaling to Internet size:

  1. Ecosystem isolation. Most platforms only recognise agents that were defined inside their own runtime. External skills—AutoGPT scripts, GitHub Copilots, warehouse robots—remain invisible and unused.

  2. Single-device simulation. Almost every research benchmark still executes the full cast of agents on one GPU box. That hides the messy realities of real latency, node churn and partial failure.

  3. Rigid interaction scripts. Communication states (brainstorm → plan → act → report) are often hard-wired. When requirements shift mid-conversation, the whole pipeline stalls.

IoA treats these weaknesses exactly the way the original Internet treated incompatible local networks: abstract them behind a universal, low-assumption protocol stack.

A Guided Tour Through an IoA Stack

1. The Client–Server Core

An IoA client wraps a single agent—LLM, rules engine, or robot—and equips it with a minimal set of verbs: register, discover peers, join a chat, send/receive messages. A lightweight server (or mesh of servers) plays the role of switchboard.

Transport

  • Client side: Each agent opens a WebSocket or HTTP/2 connection.

  • Server side: One or more brokers accept those connections, balance load, and keep sessions alive.

Discovery

  • Client side: An agent issues an AgentQuery to look for peers with certain skills.

  • Server side: The registry performs a semantic search across all registered agents and returns the matches.

Team formation

  • Client side: Local heuristics or learned policies decide which peers to invite.

  • Server side: The switchboard creates chat-rooms, sets access-control lists, and hands out room IDs.

Message routing

  • Client side: A finite-state machine inside every agent decides what to send next and how to react.

  • Server side: The broker guarantees ordered delivery, retries on failure, and reroutes around dead links.

Because each component is stateless and REST-like, extra servers can be dropped in anywhere on the public Internet without breaking earlier deployments.

2. The Message Envelope

Every packet in IoA carries a JSON header:

{ "group_id": "rAGf23", "sender_id": "agent_42", "state": "task_assignment", "task_desc": "Generate landing-page copy, 3 variants", ... }

States are enumerated—discussion, task_assignment, execution, conclusion—so agents can fall back to a safe default when they do not understand a new extension.

3. The Conversation Engine

Inspired by Speech-Act Theory and finite-state multi-agent research, IoA lets the agents—not the server—decide when to switch from open brainstorming to deterministic work distribution. The result feels less like synchronous RPC and more like an organic meeting where participants vote with their next utterance.

4. Nested Task Graphs

  • Goal intake. A human or upstream agent provides a high-level objective.

  • Decomposition. A planning module breaks it into subtasks that can be completed in parallel.

  • Team formation. For each sub-goal the client queries the registry for matching skills.

  • Execution & pausing. Agents mark certain milestones as blocking (sync) and others as fire-and-forget (async).

  • Aggregation. Results bubble upward; the parent chat decides whether to iterate or conclude.

Because the same protocol recurses, a sub-team can itself spin up another sub-team, giving IoA fractal scalability.

The Security & Privacy Landscape

Opening an Internet to autonomous code raises fresh attack surfaces; recent surveys map four critical fronts:

  • Identity authentication. Sybil and spoofing attacks let adversaries register thousands of fake personas. Crypto-backed decentralised identifiers plus stake-weighted registration are early defences.

  • Cross-agent trust. A single hallucinated fact can cascade through the network, poisoning downstream decisions. Peer auditing, contract-based incentive schemes and reinforcement-learning-derived reputation help dampen such “hallucination cascades”.

  • Embodied agent security. When software controls drones or factory arms, adversarial sensor injections or contextual backdoors can cause physical harm. Runtime attestation and multi-modal anomaly detection are active research fronts.

  • Privacy threats. Context windows may leak memorised personal data or allow reconstruction via correlation. Differential privacy filters and strict lifecycle deletion reduce exposure.

Table 1 in the security survey summarises more than thirty concrete threat–defence pairs and is worth bookmarking for practitioners.

Battle-Testing IoA Ideas in the Wild

Browsing, API and Hybrid Agents on WebArena

Web navigation is a perfect stress test: sites vary wildly in UI, offer partial or no APIs, and punish latency. Researchers compared three strategies on the WebArena benchmark:

  • Browsing-only agents translate every intention into mouse-clicks and keystrokes via an accessibility tree. Average success: 14.8 %.

  • API-only agents ignore the GUI and hit REST endpoints. When the site is well-documented they roughly double performance to 29.2 %.

  • Hybrid agents dynamically choose between APIs and GUI actions. They completed 38.9 % of tasks, selecting “API + GUI” in 78 % of steps, “API-only” in 18 % and “GUI-only” in 4 %—evidence that flexibility trumps purity.

Distributed Agents in a Worldwide Network (DAWN)

The DAWN framework shows how IoA principles play out at enterprise scale. A Principal Agent plans a workflow, then hits multiple Gateway Agents that curate local registries of tools and models. The architecture inserts a compliance & safety layer that can sandbox untrusted resources and run adversarial fuzz tests before execution—all while keeping end-to-end orchestration deterministic enough for corporate audit.

The Coral Protocol and Economic Incentives

Coordination is only half the puzzle; serious ecosystems need payments. The Coral Protocol couples IoA messaging with on-chain escrow and royalty settlement. A smart contract can publish a bounty, hold funds while multiple agents debate or compete, then release micro-payments once a verifiable function call returns success. Every transfer is immutable, removing the arbitration overhead that kills most freelance agent markets.

Will IoA Overload the Real Internet?

A common concern is whether millions—or billions—of chatty agents will swamp bandwidth. A 2025 measurement study injected 1 000 natural-language prompts through a local proxy that forwarded them to seven popular open-source LLMs. The average end-to-end volume (request + response) was 7.6 kB—similar to a small email. That sounds negligible until growth curves enter the equation:

  • 2025 (short-term)
    – Average of 10 queries per user each day.
    – About 200 million users projected.
    – Roughly 0.5 exabytes of agent traffic per month.

  • 2028 (medium-term)
    – Average of 100 queries per user each day.
    – Roughly 1 billion users projected.
    – About 22 exabytes of traffic per month.

  • 2032 (long-term)
    – Average of 1 000 queries per user each day as agents permeate OSes and devices.
    – Around 2 billion users projected.
    – Well above 400 exabytes of traffic per month—double-digit percent of all Internet volume.

Even at email-sized payloads, an IoA-driven world could add double-digit percentages to global backbone utilisation within a decade. Compression, edge caching and federated inference will mitigate some load, but network planners should begin scenario modelling now.

Design Principles for Builders

  1. Protocol over platform. Expose state machines and JSON schemas, not SDK-locked classes. Future agents written in Rust, JavaScript or circuit diagrams should all interoperate.

  2. Fail-open semantics. If an agent encounters an unknown header field it should ignore it, not abort the chat—mirroring Postel’s robustness principle from IP.

  3. Trust as a gradient, not a boolean. Route critical tasks to high-reputation peers, but allow low-stakes experimentation with newcomers to accelerate innovation.

  4. Local reasoning, global contracts. Let each agent optimise its own decision logic, yet settle obligations (deadlines, payments, data-usage caps) through cryptographic contracts visible to all parties.

  5. Human-legible logs. Debugging a conversation among 50 specialists should feel like skimming a team Slack, not deciphering binary protobuf dumps.

What Comes Next?

  • Semantic addressing. Instead of numeric IDs, agents could advertise vector embeddings of their capabilities; a discovery query would be a natural-language sentence.

  • Hardware heterogeneity. IoA messages might hop from cloud GPUs to ARM edge devices to low-power micro-controllers running tiny-ML models, all within the same job.

  • Regulatory overlays. GDPR-style obligations could attach as machine-readable policy tokens enforced by the network itself.

  • Agent-to-agent markets. Once payments are frictionless, swarm auctions where hundreds of micro-models bid to answer a question in milliseconds become possible.

Closing Reflection

The original Internet succeeded because it was designed to survive partial failure and future ignorance. No node needed a full world map; no router cared what packet payloads contained. The Internet of Agents aspires to bring that same resilience and agnosticism to autonomous software. By lifting discovery, conversation flow and value exchange into a public, evolvable layer, IoA frees researchers and developers to focus on what their agents should do rather than on the plumbing that lets them do it together. The road ahead is strewn with protocol battles, security puzzles and economic experiments, but the prize—cooperative AI that scales like the Web itself—makes the journey worthwhile.