Content type
Target engines
Recommendations synthesize per-engine retrieval behavior from the RAG and recency research: citation depth, freshness windows, and structure/schema preferences. Directional guidance, not engine documentation.
How this works
The major engines do not retrieve or cite the same way. Claude cites deeply (~13 sources) and rewards long-form methodology; Perplexity is near real-time and rewards fresh data; ChatGPT favors broad consensus and comparison structures; Google AI Overviews are schema-driven. Pick your targets and content type to get the structure, schema and refresh cadence each engine rewards.