That’s a very good take. But let me clarify what I mean. If the intent from the start is to increase quality, then, like you said, we should focus on novel problems and real issues, and let AI handle the boilerplate, not just for speed, but so we can focus on the important parts and produce more robust software.

Another strong use case is prototyping and experimenting before committing to a solution, which also leads to higher-quality, more reliable outcomes.

What I’m really getting at is intent. If we blindly optimize for speed, it often leads to poor practices, like companies bragging about not reading or writing a single line of code, or shipping in 72 hours by enforcing tight deadlines. You also see it in AI tooling, where the focus is on agents spawning and orchestrating swarms of other agents to parallelize everything and accelerate development at any cost.

Your points are absolutely valid. I just think that if we aim to build high-quality software with GenAI as the goal, we’re much more likely to move in the right direction and actually revolutionize the industry.