- AI slop originates from the codebase, affecting AI's output quality based on known patterns.
- AI shifts software economics by favoring clear, common patterns over proprietary or inconsistent systems, leveraging training data advantages.
- Popular tech stacks benefit AI due to extensive examples in training data, while proprietary languages require additional teaching within limited context.
- Workflow comparison shows AI performs better with consistent, well-established codebase patterns versus inconsistent, legacy systems needing extra context.