Three core components—tools, memory, and repository context—drive the effectiveness of coding agents. These systems integrate LLMs with external environments to handle complex software engineering tasks. By grounding models in specific codebase history, developers reduce hallucination rates. This architectural approach transforms static text generation into functional, autonomous software development workflows.