When you're building out a suite of browser-based developer tools, there are always those utilities that feel inevitable—like someone will eventually need them so you might as well be the one who builds them first. For DEV.to author ggwork, that utility was a geometry calculator: area, perimeter, volume calculations for common shapes and solids.

The AI-Assisted Development Experiment

Rather than brute-forcing through formulas and edge cases manually, the developer turned to AI assistance for what should have been a straightforward implementation. The approach combined AI-generated code with careful human review—a workflow many of us are settling into as these tools mature.

What Actually Worked Well

According to the write-up, AI handled several aspects of the project effectively. Basic formula implementations came through correctly, and boilerplate structure was generated reliably. The ability to quickly scaffold out multiple calculation functions for different shapes apparently saved meaningful time compared to writing everything from scratch. The author notes that AI also helped with handling unit conversions—a notoriously tedious aspect of calculator development where human attention tends to drift after the first few implementations.

Where Things Got Tricky

Not everything was smooth sailing. The article details specific cases where AI-generated solutions contained subtle errors or didn't account for edge cases properly. Debugging these issues required stepping through calculations manually—work that might have been faster without AI involvement in the first place. The author specifically mentions struggling with certain volume calculations where the AI approach didn't align with expected mathematical conventions, requiring significant rework before things worked correctly.

Key Takeaways

  • Basic formula implementations: solid foundation to build from
  • Edge cases and error handling: still requires human attention
  • Unit conversion logic: benefits from AI assistance but needs verification
  • Complex volume calculations: AI may introduce subtle errors that are hard to catch
  • The approach works best as a starting point, not a finished product

The Bottom Line

This is the kind of practical, grounded post-mortem the dev community needs more of. AI coding assistants are genuinely useful for accelerating development work—but treating their output as a first draft rather than finished code remains essential. The developers who'll get the most value from these tools are the ones who know enough to verify what they're given.