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Learn about the evolution from shallow to deep agents in this 19-minute tutorial that explores advanced agentic systems beyond basic LLM-tool loops. Discover how shallow agents, which simply cycle through language model calls and tool usage, often struggle with complex task planning and execution over extended periods. Understand the defining characteristics of deep agents, including their enhanced ability to conduct thorough topic exploration, develop sophisticated planning strategies, and maintain execution consistency across longer time horizons. Explore real-world applications of deep agents in two primary domains: deep research capabilities demonstrated by systems like OpenAI's Deep Research, and advanced coding functionalities found in tools like Claude Code and Manus. Gain insights into why traditional langchain architectures may fall short for complex tasks and how deep agent systems address these limitations through improved planning and execution mechanisms.
