Since 2024, the trend of integration between AI and Web3 has become increasingly evident. We have witnessed the flourishing development of multiple technology 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 groups, and business paths are distinctly different.
This article focuses on four mainstream directions: basic resource type, data protocol type, developer tool type, and content creation type, and analyzes their functional layout and ecological connection methods through typical projects, with special attention to the rise of 'creator collaboration AI protocols', bringing new possibilities to creators and project parties.
One, Scanning Mainstream AI+Web3 Projects in the Market: Four Typical Structures
Looking at the current market, we can roughly classify AI+Web3 projects into four categories:
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 launched a subnet system to strengthen model division of labor and on-chain governance, Aethir provides enterprise-grade edge GPU networks, Render has accumulated a rich node ecosystem in 3D rendering resources, and Filecoin promotes data certification and training data circulation with FVM and NFT standards.
2. Data and Content Protocol Type
Representative Projects: Story Protocol, Grass
These protocols focus on on-chain rights confirmation, data incentives, and content licensing mechanisms. Story focuses on creator IP authorization paths, while Grass uses plugins to collect web data and give feedback to users.
3. Developer and Platform Tool Type Protocols
Representative Projects: Virtuals, Injective, NEAR, Internet Computer
Focusing on programmable capabilities such as API, SDK, and on-chain containers, serving B-end developers. Virtuals provides vAgent registration and revenue mechanisms, Injective implements strategy execution frameworks in AI quantification and DeFi scenarios, NEAR and ICP provide high-performance contract environments suitable for AI model deployment.
4. Content Creation and Product Landing Type Protocols
Representative Project: AKEDO
Such protocols emphasize AI and user interaction, focusing on creative content, product output, and social dissemination, representing the path where AI+Web3 is most strongly perceived by users.
Two, The Rise of Content Creation Type AI Protocols: Why Is It Worth Attention?
With the gradual popularization of Prompt engineering and Agent orchestration capabilities, the trend of AI moving from basic capabilities to creative execution is increasingly evident. The advantages of content-type protocols include:
· Powerful AI content generation capability, low threshold, fast feedback
· More suitable for embedding in social channels, easy to form traffic fission
· Can build a closed-loop economy of 'works - monetization - re-creation'
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).
Three, Observational Case: The Three-Way Content Collaboration Flywheel of AKEDO
1. Case Status: Achieving Product Landing and Millions of Interactions
AKEDO is a creation platform built on an AI multi-agent collaboration mechanism, allowing users to generate runnable and interactive content through natural language commands, forming a creation flywheel through token incentives, work dissemination, and community interaction.
Its product closed loop mainly includes:
· Users can quickly generate frameworks and plots by calling AI modules through natural language;
· Supports visual editing, lowering the creation threshold;
· The platform can be embedded and operated in social scenes such as web pages and X;
· Creators, players, and disseminators can all earn $AKE token benefits, 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 real usage willingness and content consumption paths of users. 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 of 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 creator platform attributes, AKEDO is exploring extending its capabilities to project party services:
· AI-driven content education: The platform will support Web3 teams in generating worldview content and interactive tutorials through AI customization, enhancing user stickiness and project narrative consistency;
· Project Zone Mechanism: Build exclusive IP content incubation areas to help projects accumulate content assets and feed back community growth;
· Bidirectional Incubation Capability: Combining 'User Creation × Project Content', realizing on-chain originality and mutual empowerment of official ecosystems.
This evolutionary route is expected to make AKEDO an 'AI medium layer' aimed at content developers, project operators, and brand curators, linking tools, content, and value in a three-dimensional space.
Four, Conclusion: Product Certainty Under Multi-Path Symbiosis
The explosion of the AI+Web3 ecosystem requires not only models and hardware foundations but also real and usable interactive products and application scenarios. Creative protocols represent the shortest path to connect AI capabilities and user needs.
Among many protocols, AKEDO demonstrates an evolutionary direction from 'tool' to 'platform' through productized practices, tokenized incentive design, and collaborative expansion aimed at B+C. The protocol that can truly serve creators, project parties, and users from three ends may become the most vital link of AI landing in Web3.
