Claude Code vs Codex vs Cursor: Pick the AI Coding Tool That Matches Your Workflow

1. Claude Code Suits Terminal-Heavy Developers

The author, an embedded systems engineer with years of STM32, ARM-Linux, and driver development experience, finds Claude Code natural because it lives inside the terminal and the code repository. It can read projects, edit files, run commands, add tests, and codify personal workflows via project rules, Skills, MCP, and Sub-agents. This approach favors developers who prefer control and are comfortable with Shell, Makefiles, logs, and compilation scripts. However, the tool's freedom demands that the user understands the architecture, context, and risky areas; the more the developer knows the system, the better Claude Code performs. For those unfamiliar with the terminal, the learning curve feels steep.

2. Codex Acts Like an Independent Engineer

Codex is described as an increasingly autonomous engineer. Instead of asking for single functions, the author delegates complete tasks such as: "Refactor this module, keep the interface unchanged, add tests, and check for compatibility issues." The focus shifts from code aesthetics to whether the tool can drive the entire task forward. This is valuable for embedded development where a single issue may span drivers, application layer, device trees, config files, build systems, and legacy code. The author now asks Codex to first map call chains, list relevant files, and identify impact zones before making changes—reducing risk compared to immediate, sweeping edits.

3. Cursor Remains the Easiest On-ramp

Cursor stays closest to existing editor habits. Code, file tree, terminal, diff, and Agent all reside in one workspace, requiring almost no new workflow learning. For a first-time AI coding user, Cursor is the easiest entry point. It has evolved beyond "VS Code with AI" toward multi-agent, cloud tasks, and project-wide context, aligning with the same direction as the other two tools: turning AI from a code generator into a partner that completes whole development tasks.

4. Selection Guide Based on Work Habits

Choose Claude Code if you are a heavy terminal user doing backend, Linux, scripting, infrastructure, or ARM-Linux/driver work.

Choose Codex if you prefer handing off a complete task and letting the AI read the project, drive execution, and handle emerging issues autonomously.

Choose Cursor for the lowest learning curve; it integrates editing, agent, diff, and terminal in one daily-driver application.

5. Conclusion: The Differentiator Is the Developer

The gap between the three tools will likely shrink as all converge on agents, long-running tasks, parallel execution, and project context. The real differentiator becomes the programmer's own skills: task decomposition, context provision, result judgment, and knowing when to let AI act versus when to intervene manually. After years of embedded development, the author concludes that tools will keep changing, but deep system understanding remains the lasting asset—formerly used to write code, now used to direct AI to write code.