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Deep Research Agent(DRA)
A composite long-horizon research architecture that clarifies the user's intent, drafts an explicit research plan, then runs an iterative search, read, and evaluate-gaps loop across many sources (often via parallel subagents) before synthesizing a single long-form report with inline citation attribution. This is the assembled archetype behind OpenAI Deep Research, Gemini Deep Research, and Anthropic Research, with its own survey literature. Distinct from `agentic-rag-systems`, which applies retrieval decisioning inside a single pipeline rather than running a multi-round, plan-driven report synthesis. Distinct from `supervisor-worker-pattern`, which is generic orchestration with no research-specific plan, gap-check, or citation pass.
In 30 seconds
- What
- Clarifies intent, drafts a research plan, then iteratively searches, reads, and evaluates gaps across sources before synthesizing a cited report.
- When to use
- Multi-source research questions requiring adaptive exploration, explicit gap-checking, and traceable attribution before delivering a comprehensive synthesis.
- Watch out
- High token and latency cost from multiple rounds, parallel searches, and re-planning; citation accuracy degrades if sources are not carefully tracked through each loop.
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Deep Research Agent: Overview
A composite long-horizon research architecture that clarifies the user's intent, drafts an explicit research plan, then runs an iterative search, read, and evaluate-gaps loop across many sources (often via parallel subagents) before synthesizing a single long-form report with inline citation attribution. This is the assembled archetype behind OpenAI Deep Research, Gemini Deep Research, and Anthropic Research, with its own survey literature. Distinct from `agentic-rag-systems`, which applies retrieval decisioning inside a single pipeline rather than running a multi-round, plan-driven report synthesis. Distinct from `supervisor-worker-pattern`, which is generic orchestration with no research-specific plan, gap-check, or citation pass.
- Explicit intent clarification before planning
- Drafted research plan that decomposes the question
- Iterative search, read, and gap-evaluation loop
- Parallel subagents exploring separate sub-questions
- Adaptive re-planning that pivots on findings
- Long-form synthesis with inline citation attribution
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References
The papers, specifications, and repositories this pattern is based on.
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