Why Learn Programming When AI Can Code?

AI can generate a feature, edit a repository, and pass its tests in minutes. But passing tests does not tell you whether the program is correct, scalable, maintainable, or even solving the right problem. This video follows one unread-message counter from a convincing demo into production. A simple scan becomes too expensive as message history grows. A stored counter fixes the cost, then concurrent updates lose data. A retry after a failed response can apply the same update twice. Each fix exposes a deeper question about what “correct” should mean for the product. The point is not that AI cannot write code. It can. The point is that writing code was never the whole job. As generation gets cheaper, understanding assumptions, costs, failure modes, and tradeoffs matters more. Chapters: 0:00 The feature that looks finished 0:43 Correct, but too expensive 1:23 Fast, but sometimes wrong 2:08 What does correct mean? 3:03 The work moved upward 4:17 What programming means now 7:40 Use AI without outsourcing understanding 🔴 New CS explainers every week. Subscribe for more. 📸 Instagram: @base_case_01 #programming #ai #softwareengineering