LangGraph Podcast Summaries
LangGraph on Yedapo: 3 summarized podcast and YouTube episodes. Each includes key takeaways, core concepts and notable quotes with timestamps.
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.
UiPath for Coding Agents: Build Scalable Enterprise Applications
Krish Naik
Jun 5, 2026
UiPath does not compete with AI coding agents like Claude Code or OpenAI Codex; it acts as an orchestration layer. By integrating via agent skills, it takes raw code and wraps it in essential enterprise features including governance, compliance, human-in-the-loop validation, and security guardrails, enabling teams to move from prototype to production.
Key insight: UiPath provides a 'coded' agent type that keeps local IDE development and cloud-based studio environments in perfect sync, meaning manual code changes in VS Code or Cursor automatically update the visual workflow interface.
Complete Agentic AI Course In 10 Hours- Langchain, Langgraph, RAG,Vectorless RAG, Guardrails,Evals
Krish Naik
May 21, 2026
This comprehensive guide covers the evolution of GenAI into agentic AI, emphasizing practical implementation with LangChain and LangGraph. It details building sophisticated agents, integrating tools, managing conversation memory, and utilizing modern workflows like middleware for guardrails, streaming, and human-in-the-loop oversight.
Key insight: Using the 'UV' package manager, written in Rust, can make Python environment creation and library installation significantly faster than traditional tools like pip or poetry.