A developer's reflection on his abandoned projects reveals a stark shift in software development. He found his GitHub graveyard filled with completed but unused projects, from an Enigma machine to a text adventure creator. The rise of agentic coding tools like Cursor’s plan mode enables rapid execution, often before deep understanding can take root. This trend forced a personal reckoning about the value of scattered work versus focused mastery.

The author revisited his decade-long text adventure project, a failure that taught crucial lessons now outdated. He learned that following standards without context, mirroring real-world models, and over-building features were mistakes. However, these hard-won insights came from an era before LLMs and instant coding answers. Today, the industry's pace means the lessons for developers are likely entirely different, shaped by new tools and expectations.

Execution has become cheap, but deep learning remains expensive and personal. AI excels at validating ideas and shipping code quickly, letting developers skip the painful mistakes that forge real skill. For those wanting to ship faster, starting with the machine makes sense. But for genuine craft, the struggle is non-negotiable. The future belongs to those who balance AI's speed with the deliberate, hard-earned understanding of their domain.