Three primary components—tools, memory, and repository context—enable LLMs to function as effective coding agents. These elements allow models to interact with files and track state across complex codebases. Integrating these systems reduces hallucination and improves logic. Developers can now build more reliable autonomous workflows by prioritizing context retrieval over raw model size.