Building Your First AI Agent with LangChain (Part 1: The Theory)

Semantic Tracing in LLM-Based Multi-Agent Systems Using LangChain, LangGraph, and LangSmith for AI Governance

Autonomous multi-agent systems built on large language models exchange goals, constraints, evidence commitments, and tool-mediated actions through natural-language handoffs. Across hops, semantic meaning may drift, constraints may weaken, unsupported claims may propagate, and organizations may...

Building Your First AI Agent with LangChain (Part 1: The Theory)

Last Updated on July 27, 2026 by Editorial Team Author(s): A.Venkatesh Originally published on Towards AI. 1. Traditional LLMs vs. Autonomous Agents Most AI tutorials teach you how to build basic chatbots. This guide covers how to build an AI Agent — a system that reasons, chooses tools, and takes action to complete multi-step tasks. Traditional LLM vs AI AgentsThe article explains how AI agents differ from traditional LLMs by adding an action l…