Three primary components—tools, memory, and repository context—enable LLMs to function as effective coding agents. These systems move beyond simple chat by integrating RAG and execution environments. This architecture allows agents to navigate complex codebases independently. Developers can now build autonomous workflows that reduce manual boilerplate and debugging time.