Your agent wants to search like a 2010 quant
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Agent search techniques, directly applies to AI agent orchestration.
AI agents are entering a third stage of information retrieval, moving beyond vector databases and hybrid search to 'search as code'—where agents autonomously construct complex, multi-step queries using structured fields, filters, and ranking options. Perplexity's approach demonstrates that agents, unlike lazy human users, can leverage expert-level search tactics (e.g., date ranges, field-specific queries, aggregations) to produce significantly better results. Implementing this is straightforward: models already understand query languages and only need a textual description of available search capabilities to connect intent to precise retrieval.