| Something maybe worth thinking about. If you are relying on understanding every single line of code, then maybe you should examine your modularity and testing norms. I don’t know about you, but the next day, I can’t realistically claim to actively hold an understanding of every line of code I wrote the day before. But AI can review 10Kloc and hold it in context with flawless retrieval. I cannot do that. If you have the right structural framework and don’t approach it as a crutch but rather an amplifier, you can actually improve code quality and documentation while multiplying productivity, and you also don’t get cognitive atrophy out of the deal. Also, previously unrealistic testing jigs are now trivial to implement, so I can test my code way beyond the point where I would have shipped it before. AI , like people, makes mistakes. But using AI enables you to pivot to building the infrastructure that assures that no mistakes can escape the lab. That becomes your entire focus, instead of being a burdensome and usually neglected operational overhead. It’s definitely easy, even tempting, to “hold it wrong” though. |