Complete Deep Agents Course With Langchain In 3 Hours
Krish Naik
Jun 6, 2026
Krishna explains that while standard LLM agents simply loop between inputs and tools, 'Deep Agents' utilize explicit planning, sub-agent delegation, and persistent file-system memory to solve complex, multi-step tasks. By integrating planning modules, persistent memory, and specialized skills, developers can create AI agents capable of autonomous research and report generation that mimics advanced systems like Claude Code.
Key insight: Deep agents operate on 'context engineering' where specialized capabilities (skills) and instructions are only loaded when relevant to a specific task, keeping the agent's active memory clean and reducing token consumption.
