As AI coding assistants become ubiquitous, a growing problem is the generation of massive, repetitive, and poorly structured code—sometimes 8,000 lines of near-duplicate logic from a single prompt. This article, based on a decade of experience with a 100,000-line C++ codebase, proposes three engineering disciplines to counter this trend. First, 'ancient foundation' means establishing a stable, well-tested core architecture before letting AI generate code around it. Second, 'granularity is life and death' emphasizes that AI works best when constrained to small, single-responsibility units; large functions invite chaos. Third, 'write thin glue' advocates for minimal, explicit integration code between AI-generated components, avoiding opaque abstractions. The author also briefly mentions a personal tool, GufaForge, that automates these rules, but the principles themselves are tool-agnostic and immediately applicable. For engineering leaders, this framework offers a way to harness AI's productivity gains without sacrificing long-term maintainability.
A senior engineer shares three hard-won principles for controlling AI-generated code quality in large C++ projects: enforce a solid architectural foundation, keep code units small and focused, and write minimal glue code. The post is grounded in a 10-year, 100,000-line codebase and offers actionable advice for any team using AI coding assistants. This matters because AI code generation is exploding, but most teams lack the engineering discipline to prevent massive technical debt.