The 'Don't Repeat Yourself' (DRY) principle creates complex abstractions that are difficult for AI agents to navigate. A flatter, duplicated code structure is easier for an AI to parse and modify safely, as it contains the 'blast radius' of any changes, making it more efficient for machine maintenance.
In the AI era, technical debt isn't 'ugly' code but anything that slows an AI agent's feedback loop. This includes slow tests, messy system boundaries that the AI will replicate, and poor runtime performance. The focus shifts from human readability to machine-drivable efficiency and safety.
As AI agents generate code, human review must shift from syntax to instructions. In 'Structured Prompt Driven Development,' prompts become version-controlled artifacts. The focus is on the quality of instructions and the automated tests that validate the output, making code a disposable implementation detail.
Microservices were primarily a solution for organizing human teams and managing cognitive load (Conway's Law). Since AI agents lack these limitations, the architectural rationale weakens. Companies can revert to monolithic repositories to avoid network overhead and complexity, as an AI can manage a codebase far too large for any human.