Perplexity's "Search as Code" lets AI models write their own search pipelines instead of calling fixed APIs
Perplexity's new architecture replaces rigid search APIs with Python-based routines written by AI models.
The "Search as Code" system allows agents to handle their own filtering and deduplication within a sandbox environment. By moving logic into the model's control, Perplexity reports improved benchmark performance and up to 85% lower token costs compared to traditional API-driven search pipelines.