Coding agents combine tool use, memory, and GitHub repo context to sharpen LLM performance. By chaining OpenAI APIs and recalling prior steps, they reduce hallucinations and speed up debugging. Developers can plug these agents into IDEs or CI pipelines, turning large language models into practical helpers that learn from code history. The result is faster, more reliable code generation.