"Maybe later" was a feature

That framing landed with people because it matches what they are already seeing. Several described how writing a feature by hand forces you to confront edge cases, awkward workflows, and hidden dependencies early. When an LLM can one-shot a plausible implementation, that reality check arrives later, after the feature exists and starts attracting dependencies, users, and political baggage. The strongest practical point was not that AI makes bad ideas, but that it shortens the distance between vague idea and production artifact so much that teams skip the judgment step. The consensus was that this is mostly a product and process problem, not a model problem. People kept coming back to YAGNI, minimal versions, shell-script-first workflows, and using AI for testing, analysis, and bug fixing instead of feeding backlog inflation. A few pushed back that scarcity also hid good work, especially internal tooling, security fixes, and quality-of-life improvements that were always worth doing but never prioritized. Even there, the useful reading was the same. Cheap code does not remove the need to choose. It makes the cost of choosing badly show up later, as bloat, harder deletions, and a product full of features that each matter deeply to a different slice of customers.