Building an Autonomous Coding Assistant: A LangGraph.js Capstone Guide

The dream of autonomous software engineering is no longer science fiction. It's a practical architectural challenge. Instead of asking an AI to "write code," we are now building systems that can perceive a codebase, plan a multi-step implementation, execute terminal commands, and iteratively debug their own work. This is the shift from simple chatbots to true agentic workflows . In this capstone guide, we will dissect the architecture of an autonomous coding assistant. We will explore how to move beyond monolithic LLM calls to a system of specialized agents—Planners, Coders, and Testers—orchestrated via LangGraph.js . By the end, you will understand how to build a self-correcting loop that mimics the workflow of a human developer. The Architecture of Autonomy: From Monoliths to Microservices To build a robust autonomous agent, we must abandon the "one-shot" prompt approach. Asking a single Large Language Model (LLM) to "write a bug-free Python script" is akin to asking a single develop