ElemontCapital X Development Engineering
Technical expertise for developing and extending the X recommendation engine, focusing on the Grok-powered Phoenix model, Rust candidate pipelines, and the removal of hand-engineered features.
Context
The modern X algorithm prioritizes a "No Hand-Engineered Features" philosophy. Relevance is learned directly from user engagement sequences using a transformer architecture.
For technical deep-dives, see:
What it does
- Implements Grok-Native Components: Guidance on integrating with the Phoenix transformer for multi-action prediction (Like, Repost, Reply, etc.).
- Architects Candidate Sources: Logic for the two primary retrieval engines: Thunder (In-Network) and Phoenix Retrieval (Out-of-Network).
- Enforces Pipeline Order: Ensures components follow the strict sequence: Query Hydration -> Sourcing -> Hydration -> Pre-Scoring Filters -> Scoring -> Selection.
- Optimizes for Parallelism: Leverages Rust's async/await to execute independent hydration and sourcing tasks concurrently.
Guidelines
- Candidate Isolation: During scoring, ensure candidates cannot "attend" to each other in the transformer. This maintains score consistency and enables batching.
- No Heuristics: Avoid adding manual "if/then" rules for relevance; the Phoenix model should handle weightings through learned engagement probabilities.
- Hydration Efficiency: Fetch only necessary metadata (text, media, author status) during the Candidate Hydration stage after initial sourcing to minimize I/O.
- Safety First: All content must pass through
VisibilityLib(Rust) for legal compliance and safety filtering before reaching the user.
Example Trigger Prompts
- "/gen-thrift new ranking signal"
- "/gen-thrift scaffold Rust Filter trait"
- "Add a new engagement signal to Phoenix prediction"
- "Show Rust implementation for Thunder candidate source"
- "Explain 'No Hand-Engineered Features' in ranking update"
- "How is candidate isolation applied in transformer attention?"