Perplexity launches 'Search as Code' for agents
Perplexity has introduced 'Search as Code' (SaC), a programmable search architecture that allows AI agents to write and execute Python code using low-level search primitives. By replacing multi-turn tool calling with sandboxed execution, the new system reduces latency and token consumption for complex retrieval tasks.
Hot Take: Search is no longer a static endpoint; it is a programmable runtime library. By shifting to Search as Code, Perplexity aims to own the developer framework layer for AI agents, transforming search APIs from black-box document retrievers into sandbox-executable SDKs.
- –Sandboxed execution of search primitives enables massive efficiency improvements for complex multi-step reasoning.
- –Condensation of search loops into single-run generated scripts drastically reduces token consumption and network round trips.
- –Elevates agent resilience by letting LLMs dynamically write, test, and debug their own custom data aggregation algorithms.
DISCOVERED
11d ago
2026-06-01
PUBLISHED
11d ago
2026-06-01
RELEVANCE
AUTHOR
AravSrinivas