Tools: macOS Hardware Info : AI performance benchmarking

What I Built ## My Experience with GitHub Copilot CLI GitHub Copilot CLI Challenge Submission This is a submission for the GitHub Copilot CLI Challenge https://github.com/CodeGeekR/macOS-hardware-info I built macOS Hardware Info – a unified diagnostic tool that consolidates SSD health monitoring with AI performance benchmarking. The tool gives you real-time S.M.A.R.T. data, calculates Total Bytes Written in Terabytes, measures actual disk speeds with 1GB benchmarks, and runs AI performance tests on CPU, GPU, and Apple's Neural Engine. What makes it special is the native Apple Silicon support – it uses multi-layer fallback detection for T2, M1, M2, M3, and M4 chips, handling Apple's proprietary controllers that standard tools miss. Built it in under 5 hours and got all 18 tests passing. It means a lot to me because it proves you can write professional, production-ready code fast when you have the right workflow. Honestly? Game-changer. I was skeptical at first, but Copilot CLI turned what would've been a full weekend project into a sub-5-hour sprint. Log Page 0xC0. - It auto-completed type annotations as I wrote functions. No more context-switching to docs for dict[str, Any] | None syntax. - Created 18 unit tests by describing what I wanted to test. It caught edge cases I hadn't thought of (like the power_cycles vs power_cycle_count field issue). I had a bug where power cycles showed "N/A". Copilot suggested log.get('power_cycle_count') or log.get('power_cycles') – turns out different SSDs use different field names. That's knowledge I would've spent 30 minutes Googling. I'd describe intent in comments, Copilot would draft the code, I'd review/adjust, then move to the next function. Felt like pair programming with someone who'd read the entire smartmontools documentation. The speed boost wasn't just about typing faster – it was about staying in flow. No mental context switches, no documentation rabbit holes, just continuous forward progress. Finished with time to spare for proper documentation and a professional README. Would I have built this without Copilot CLI? Sure, eventually. But it would've taken 2-3 days instead of one afternoon, and I'd probably have skipped the comprehensive tests and detailed docs due to time pressure. Copilot CLI doesn't replace thinking, but it eliminates the boring parts so you can focus on architecture and problem-solving. That's where the real engineering happens. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse CODE_BLOCK: - It mapped out the architecture, identified duplicate code, and suggested a clean dataclass-based structure. Saved me hours of manual refactoring. - When dealing with Apple's proprietary SSD controllers, I'd type a comment like "handle Apple NVMe vendor logs" and it would generate the multi-method fallback strategy. It knew about the IOKit framework and NVMe Enter fullscreen mode Exit fullscreen mode CODE_BLOCK: - It mapped out the architecture, identified duplicate code, and suggested a clean dataclass-based structure. Saved me hours of manual refactoring. - When dealing with Apple's proprietary SSD controllers, I'd type a comment like "handle Apple NVMe vendor logs" and it would generate the multi-method fallback strategy. It knew about the IOKit framework and NVMe CODE_BLOCK: - It mapped out the architecture, identified duplicate code, and suggested a clean dataclass-based structure. Saved me hours of manual refactoring. - When dealing with Apple's proprietary SSD controllers, I'd type a comment like "handle Apple NVMe vendor logs" and it would generate the multi-method fallback strategy. It knew about the IOKit framework and NVMe