Since the beginning of 2024, the trend of integration between AI and Web3 has become increasingly evident. We have witnessed the vigorous development of multiple technical routes, from decentralized reasoning networks (such as Bittensor), GPU market protocols (such as Render, Aethir), to content rights confirmation and IP market protocols (such as Story Protocol, Grass). Although these projects share the underlying logic of “AI-native incentives + blockchain verifiability,” their technical focuses, target audiences, and commercial paths are distinctly different.

This article focuses on four mainstream directions: basic resource type, data protocol type, development tool type, and content creation type. It analyzes the functional layout and ecological connection methods through typical projects, with particular attention to the rise of the “creator collaboration AI protocol,” which brings new possibilities for creators and project parties.

1. Scanning mainstream AI + Web3 projects in the market: Four typical structural categories

In the current market, we can roughly categorize AI + Web3 projects into four types:

1. Basic Resource Type Protocol

Representative projects: Bittensor, Aethir, Render, Filecoin

These projects provide underlying resources for AI model inference and training, covering GPU computing networks, data storage, and model collaboration incentives. Bittensor introduces a subnet system to strengthen model division of labor and on-chain governance, Aethir offers an enterprise-level edge GPU network, Render accumulates a rich node ecosystem in 3D rendering resources, while Filecoin promotes data certification and training data circulation with FVM and NFT standards.

2. Data and Content Protocol Type

Representative projects: Story Protocol, Grass

This type of protocol focuses on on-chain rights confirmation, data incentives, and content licensing mechanisms. Story focuses on the IP authorization path for creators, while Grass uses plugins to collect webpage data and provide feedback to users.

3. Developer and platform tool protocol

Representative projects: Virtuals, Injective, NEAR, Internet Computer

Focusing on programmable capabilities such as API, SDK, and on-chain containers, serving B-end developers. Virtuals provide vAgent registration and revenue mechanisms, Injective implements strategy execution frameworks in AI quantification and DeFi scenarios, while NEAR and ICP offer high-performance contract environments suitable for AI model deployment.

4. Content Creation and Product Implementation Protocol

Representative Project: AKEDO

This type of protocol emphasizes the interaction between AI and users, focusing on creative content, product output, and social dissemination, representing the current strongest path of AI+Web3 in user perception.

2. The Rise of Content Creation AI Protocols: Why is it Worth Paying Attention?

With the gradual popularization of Prompt engineering and Agent orchestration capabilities, the trend of AI moving from basic capabilities to creative execution is becoming increasingly evident. The advantages of content-based protocols are:

· Powerful AI content generation capabilities, low threshold, quick feedback

· More suitable for embedding in social channels, easy to create traffic fission.

· A closed-loop economy can be built around “creation-monetization-recreation”.

In this direction, AKEDO is one of the few representative projects that has completed the launch of a prototype product and achieved user interaction verification (DYOR).

3. Observation Case: AKEDO’s Tri-Directional Content Collaboration Flywheel

1. Current status of the case: Achieving product implementation and one million interactions

AKEDO is a creative platform built on an AI multi-agent collaboration mechanism that allows users to generate runnable and interactive content through natural language instructions, and forms a creative flywheel through token incentives, work dissemination, and community interaction.

Its product closed loop mainly includes:

· Users can quickly generate frameworks and plots by calling the AI module using natural language;
· Supports visual editing, lowering the creation threshold;
· The platform can be embedded and run in web pages, X and other social scenarios;
Creators, players, and disseminators can all earn $AKE token rewards, achieving a win-win situation for all parties.

Unlike most projects that are still in the “protocol vision” stage, AKEDO has accumulated millions of on-chain interactions and community participation through actual operations, demonstrating the willingness of real users to use and consume content. Here are some publicly available data:

· 2M TG subscribers, 303K X followers;
· 1M on-chain interactions, DappBay’s highest historical ranking is 4th;
· The user interaction heat for interactive content within the platform reaches 1.2M;
· Collaborated with 8 leading IPs (such as BNB, Mew, etc.)

2. Platform evolution: closing the loop towards IP services

While maintaining the attributes of a creator platform, AKEDO is exploring extending its capabilities to serve project parties:

· AI-driven content education: The platform will support Web3 teams in customizing and generating worldview content and interactive tutorials through AI, enhancing user engagement and project narrative consistency;

· Project Zone Mechanism: Build a dedicated IP content incubation area to help projects accumulate content assets and feed back community growth;

· Two-way incubation capability: Combining “user creation × project content” to achieve mutual empowerment between on-chain originality and the official ecosystem.

This evolutionary path is expected to make AKEDO an “AI media layer” for content developers, project operators, and brand curators, bridging the circulation loop in the three-dimensional space of tools, content, and value.

IV. Conclusion: Product Determinism under Multi-Path Symbiosis

The explosion of the AI+Web3 ecosystem not only requires models and hardware foundations but also relies on truly usable interactive products and application scenarios. Creative protocols represent the shortest path connecting AI capabilities and user needs.

Among many protocols, AKEDO demonstrates an evolutionary direction from “tool” to “platform” through productized practices, tokenized incentive designs, and collaborative expansion oriented towards B+C. In the future, protocols that can truly serve creators, project parties, and users may become the most vital link in the implementation of AI in Web3.

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