Coding agents integrate tool-use, memory, and repository context to enhance LLM performance. These systems move beyond simple chat by interacting directly with file systems and compilers. This architecture reduces hallucination and improves code accuracy. Developers can now build more reliable autonomous workflows by prioritizing context retrieval over raw model size.