Uploaded November 2025 | Updated September 2026, 2 weeks ago
Deep agents represent an evolution beyond simple agentic systems that just loop through LLM calls and tool usage. While the basic agent architecture of an langchain LLM calling tools in a loop works, it often results in "shallow" agents that fail to plan and execute complex tasks over longer time horizons.
What Makes an Agent "Deep"?
Deep agents are characterized by their ability to dive deep on topics, plan more complex tasks, and execute over longer time horizons. langchain They've emerged primarily in two domains: deep research (like OpenAI's Deep Research) and coding (like Claude Code and Manus).
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Deep agents represent an evolution beyond simple agentic systems that just loop through LLM calls and tool usage. While the basic agent architecture of an langchain LLM calling tools in a loop works, it often results in "shallow" agents that fail to plan and execute complex tasks over longer time horizons.
What Makes an Agent "Deep"?
Deep agents are characterized by their ability to dive deep on topics, plan more complex tasks, and execute over longer time horizons. langchain They've emerged primarily in two domains: deep research (like OpenAI's Deep Research) and coding (like Claude Code and Manus).
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Join Our 2.0 Data Science And GEN AI Bootcamp
krishnaik.in/liveclass2/datascience?id=8
