I think AI coding hype follows roughly four stages: 1. Amazement You try it and can’t believe how much code it generates from a few prompts. 2. Expansion You start more and more projects because shipping suddenly feels cheap and fast. This is also the phase where people start convincing everyone around them: - coworkers - management - friends in other companies because nobody wants to “fall behind” in 6–12 months. That creates a massive snowball/FOMO effect. 3. The grind phase You realize the generated code has architectural issues, sloppy mistakes, weird abstractions, duplicated logic, broken edge cases, etc. So you start: - re-prompting - switching models - increasing reasoning effort - reviewing fixes - generating fixes for previous fixes And suddenly you spend your days reviewing AI-generated pull requests instead of building software. 4. Realization You realize AI coding increases output much faster than it increases certainty. The code still needs: - review - testing - ownership - architectural understanding - long-term maintenance Usually by expensive senior engineers. And the interesting thing is: this whole cycle can take many months or even more than a year because people become socially and professionally invested in the narrative themselves. Once teams, managers, and entire companies have been convinced that this is the future, it becomes psychologically and politically very hard to later say: “Actually, the ROI is much lower than we expected.”