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Coding harness landscape

← Learning Atlas · Path 7 of 22

7 ordered steps, from Codex CLI to Devin.

AI agents and harnesses

  1. Step 1: Codex CLI

    Start with a terminal-native harness because it highlights direct project editing and command execution as the core workflow.

  2. Step 2: Claude Code

    Claude Code provides a nearby comparison point, helping learners separate the coding-agent pattern from one provider's model choices.

  3. Step 3: Aider

    Aider belongs next because it shows a Git-centered approach where the harness is tightly connected to patch review and commits.

  4. Step 4: Cline

    Cline moves the same agent pattern into the editor, so learners see how tool access changes when work happens inside an IDE.

  5. Step 5: Cursor

    Cursor broadens the view from one agent extension to an AI-first editor where chat, edits, and codebase search are integrated.

  6. Step 6: Windsurf

    Windsurf is useful here because it sits close to Cursor while emphasizing more autonomous flow and project-level awareness.

  7. Step 7: Devin

    Devin is the endpoint because it represents the more autonomous software-engineer-agent ambition beyond editor assistance.