Search is a core primitive for AI systems. Frontier models grow more capable by the month, but they still need access to fresh, accurate, and well-curated knowledge from the wider world. Search is the primary way that AI systems tap into that knowledge, and thus a foundational component of any product that needs to draw conclusions, take actions, and perform real-world work.

We believe that traditional search pipelines are increasingly outdated in the era of agents. Traditional search answers queries, but today’s agents complete tasks that can take on countless shapes. These tasks require agents to define task-specific retrieval strategies directly within their harnesses. Within Perplexity Computer, we’ve seen single tasks invoke hundreds or even thousands of retrieval operations within a few minutes: a workflow that is impossible for humans but absolutely natural for agents.

In this world, search itself must become agentic, with its building blocks accessible directly as SDKs within the agent harness. We are introducing Search as Code (SaC) as Perplexity’s new reference search architecture. — Read More