What is Agentic Search?
TL;DR
The next-generation search paradigm in which the AI loops through search → read → evaluate → re-query autonomously. The substrate behind Perplexity, ChatGPT Search, Gemini, and Genspark in 2026.
Agentic Search: Definition & Explanation
Agentic Search is the next-generation search paradigm. Where classic search returns a list of links for the user to triage, an agentic system runs the loop itself: initial search → read top sources → identify gaps → re-query → evaluate → synthesize. It's the substrate beneath Deep Research and became the default in 2024-2026. Production systems: Perplexity AI (Sonar Reasoning Pro, Pro Search), ChatGPT Search (GPT-5 + browsing), Google Gemini (SGE / AI Overviews / AI Mode), Genspark (multi-agent search), You.com (Smart Mode), Andi, and Phind (engineer-focused). Core building blocks: (1) query decomposition into sub-queries, (2) iterative retrieval, (3) source quality evaluation, (4) citation generation, (5) conversational memory across turns, and (6) tool use (calculator, code execution alongside search). Google responded with SGE → AI Overviews → 2026's official AI Mode, but Perplexity and ChatGPT have already taken 5-10% of web search share. New disciplines — AIO (AI Overviews optimization), GEO (Generative Engine Optimization), and LLMOps-for-marketing — emerged in response. It's an integrated implementation of LLM routing, multi-step planning, ReAct, and RAG, and one of the most contested frontiers of AI engineering. Content optimization for it leans on FAQ structure, structured data, strong E-E-A-T signals, and quotable one-sentence summaries.