Testing AI coding agents (2025): Cursor vs. Claude, OpenAI, and Gemini

In 2025, AI coding agents have emerged as powerful tools for software development, each excelling in different areas and catering to various engineering needs. Cursor, using Claude Sonnet 4, is praised for its speed and code quality, making it ideal for Docker/Render deployment, while Claude Code excels in rapid prototyping and offers a productive terminal user experience. Google’s Gemini CLI stands out for handling large-context refactors due to its substantial context window, and OpenAI Codex is recognized for its model accuracy, though hindered by user experience issues. The author, initially skeptical of AI tools, decided to test these agents in both boilerplate generation and real-world production environments. Cursor impressed with its clean app creation and effective error handling, while Gemini showed strength in production tasks despite struggling with boilerplate generation. Codex demonstrated high-quality output but faced UX challenges, and Claude Code, though easy to use, struggled with complex tasks. The author concludes that while AI agents are valuable, especially for error resolution and DevOps, they are best utilized by experienced engineers who can critically assess their output, and recommends them for boilerplate generation, error assistance, and deployment tasks.