Hands-On with OpenAI Codex CLI: A Knight’s Tour Walkthrough

This walkthrough uses OpenAI Codex CLI to build a small but complete project: a Python Knight’s Tour solver, tests and a Flask visualisation. The useful lesson is the workflow, not just the puzzle.

Three-phase workflow

1. Plan the solver, interfaces and acceptance criteria in natural language.
2. Implement the algorithm and web view, asking Codex to keep changes focused.
3. Verify with pytest, inspect the diff and run the app locally before accepting the result.

An AGENTS.md file records project conventions so later prompts remain consistent. Short feedback loops make it easier to catch incorrect assumptions before they spread.

Why this example works

The Knight’s Tour has a clear success condition, deterministic tests and a visual result. That makes it a practical example for learning how to guide an agent through repository changes while retaining review control.

For the hardware context behind local coding and inference, see the Mac Mini M4 vs Mac Studio benchmark.

Read the full walkthrough on malcolmlow.com.