Escaping the Quicksand Argues AI Coding Is Compounding Technical Debt Faster Than It Retires It

arXiv 2608.19674·medium signalXBlueskyLinkedInCopy link

This position paper from the formal-methods community argues that 75 years of building systems against prose specifications with test-and-debug loops left everyone on shaky foundations, and that AI-enabled engineering amplifies both sides of the ledger, cutting coding costs while rapidly increasing technical debt and automating discovery of the vulnerabilities inside it. Rather than pushing full proof of correctness, which remains hard to apply both technically and culturally, the authors argue for pragmatic combinations of testing, specification and proof. Their immediately actionable recommendation is incrementally co-developing executable-as-test-oracle partial specifications alongside prose, code and tests, which sharpens design and makes testing more discriminating; the harder ask is community investment in semantics infrastructure for mainstream languages.