Day 4: AI Agent Memory

Today’s session focused on one of the most powerful capabilities of intelligent systems, AI Agent Memory. We explored how to make AI agents more human-like by enabling them to store, recall, and summarize past interactions, creating richer and more contextual conversations. What You’ll Learn in This Video: ✅ Implementing short-term memory using LangGraph-Checkpointer ✅ Building long-term memory with LangGraph-Store ✅ Creating a chatbot with message summarization for improved context retention ✅ Designing AI agents that remember past states and respond intelligently 💡 This session is ideal for anyone interested in LangGraph, LLMs, agent design, chatbot development, and advanced AI workflows. After watching, you’ll understand how real-world AI systems use memory to maintain context and deliver better user experiences. GitHub: https://github.com/CodeByFelix/Deep-Dive-into-AI-Agent-with-LangGraph-Training