Why Software Factories Fail
TLDR ● Covered by 2 sources
A software engineer argues that fully autonomous AI code generation (lights-off software factories) fails because AI models cannot maintain codebase quality over time, despite excelling at benchmarks and rapid development; the author's company attempted this in July 2025 and experienced multiple severe outages within months that required manual intervention. The Faros AI report found that since January 2025, pull-request review quality dropped significantly, with incidents and bugs per developer increasing substantially after teams adopted AI coding tools. Companies must balance AI velocity with human oversight of code maintainability, as no amount of prompt engineering or automated testing can solve the fundamental limitation that models degrade codebase architecture without continuous human steering.
Why it matters
No amount of harness engineering can solve fundamental model-training issues, and companies should embrace their constraints rather than chase unrealistic speed improvements.
