Building Your Own Deep Research with Exa

Published on: September 23, 2025

Tags: #research #ai #agents


Traditional vs. AI-Powered User Research Process

graph TD;
    subgraph AI-Powered User Research
        direction TB
        A1[Start: User Question] --> A2[AI Generated Questions];
        A2 --> A3[AI Participant Personas];
        A3 --> A4[AI Simulated Interviews];
        A4 --> A5[AI Powered Analysis];
        A5 --> A6[Finish: Final User Research Report];
    end

    subgraph Traditional User Research
        direction TB
        B1[Start: User Question] --> B2[Create Interview Questions];
        B2 --> B3["Identify & Recruit
Participants (2-3 weeks)"]; B3 --> B4["Conduct Interviews
(1-2 weeks)"]; B4 --> B5["Analyze Responses
(1 week)"]; B5 --> B6[Finish: Final User Research Report]; end style A1 fill:#e6e6fa,stroke:#8a2be2 style A2 fill:#e6e6fa,stroke:#8a2be2 style A3 fill:#e6e6fa,stroke:#8a2be2 style A4 fill:#e6e6fa,stroke:#8a2be2 style A5 fill:#e6e6fa,stroke:#8a2be2 style A6 fill:#90ee90,stroke:#006400 style B1 fill:#e6e6fa,stroke:#8a2be2 style B2 fill:#e6e6fa,stroke:#8a2be2 style B3 fill:#ff6347,stroke:#b22222 style B4 fill:#ff6347,stroke:#b22222 style B5 fill:#ff6347,stroke:#b22222 style B6 fill:#e6e6fa,stroke:#8a2be2

AI-Powered Deep Research Workflow

graph TD;
    A[Research Question] --> B["Tool Calling (Web Search)
- Exa"]; B --> C["Retrieval Augmented
Generation (RAG)"]; C --> D["Large Language Model
(LLM) - Cerebras"]; D --> E[Answer]; style A fill:#FFDDF4,stroke:#A020F0,stroke-width:2px style B fill:#BF40BF,stroke:#8A2BE2,stroke-width:2px,color:#fff style C fill:#BF40BF,stroke:#8A2BE2,stroke-width:2px,color:#fff style D fill:#FFDDF4,stroke:#A020F0,stroke-width:2px style E fill:#98FB98,stroke:#3CB371,stroke-width:2px

Advanced Multi-Layer Research Process

graph TD;
    subgraph Advanced Research
        direction TB
        A[Research Question] --> B{Layer 1: Initial Search};
        B --> C{"Get Initial Analysis &
Identify Follow-up Topic"}; C --> D{Layer 2: Follow-up Search}; D --> E{Final Synthesis}; E --> F[Comprehensive Analysis]; end style A fill:#e6e6fa,stroke:#8a2be2,stroke-width:2px style B fill:#e6e6fa,stroke:#8a2be2,stroke-width:2px style C fill:#e6e6fa,stroke:#8a2be2,stroke-width:2px style D fill:#e6e6fa,stroke:#8a2be2,stroke-width:2px style E fill:#e6e6fa,stroke:#8a2be2,stroke-width:2px style F fill:#98FB98,stroke:#3CB371,stroke-width:2px

Anthropic Multi-Agent System

graph TD;
    subgraph Anthropic Multi-Agent System
        direction TB
        A["Lead Agent: Decomposes
Query into Subtasks"] --> B["Subagent 1: Researches
Core Concepts"]; A --> C["Subagent 2: Researches
Latest Developments"]; A --> D["Subagent 3: Researches
Applications"]; B --> E{"Lead Agent: Synthesizes All
Findings"}; C --> E; D --> E; E --> F["Final Comprehensive
Report"]; end style A fill:#4682B4,stroke:#333,stroke-width:2px,color:white style B fill:#B0C4DE,stroke:#333,stroke-width:2px,color:black style C fill:#B0C4DE,stroke:#333,stroke-width:2px,color:black style D fill:#B0C4DE,stroke:#333,stroke-width:2px,color:black style E fill:#4682B4,stroke:#333,stroke-width:2px,color:white style F fill:#98FB98,stroke:#333,stroke-width:2px,color:black

Source: How to Build Advanced AI Agents

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