On-Chain Feed Generation, Recommendation & Delivery Pipeline

Updated: 8th March 2025

RuBaRu's On-Chain Feed Generation, Recommendation, and Delivery Pipeline is designed to systematically process and personalize content delivery at scale. The architecture employs modular and extensible design principles, ensuring seamless integration of advanced functionalities over time. At its core, the feed pipeline will categorizes, tags, moderates, enriches, ranks, and personalizes content based on user configurations and behavioral patterns.

To optimize performance and scalability, we leverage the Strategy and Aggregator design patterns for constructing a unified content feed, enabling structured content ingestion from multiple sources while maintaining flexibility. Pre-built feed caching mechanisms are implemented to eliminate the inefficiencies of on-demand feed generation, reducing latency and enhancing responsiveness. This ensures a smooth and uninterrupted user experience, which is critical for content discovery and engagement, especially when a social media user's attention span is only a few seconds.

The pipeline is engineered with future-proofing in mind, supporting plug-and-play enhancements. For instance, once 64-bit WebAssembly (Wasm) support is available in Motoko, we will integrate our DeAI-powered NSFW content detection and tagging service MVP, allowing users to customize their content preferences dynamically.

By centralizing content within a unified feed, RuBaRu enhances discoverability, strengthens community interaction, and maximizes user retention. This structured and algorithmically optimized approach ensures an engaging, censorship-resistant, and personalized content consumption experience on-chain.