Every software organization faces the onboarding challenge: helping newcomers navigate complex codebases, compensate for insufficient documentation, and comprehend code they did not author. Expert walkthroughs are among the most effective forms of support, yet they are expensive, repetitive, and do not scale. We present Lacy, a hybrid human-AI onboarding system that captures expert mentoring in reusable code tours-to our knowledge, the first hybrid approach combining AI-generated content with expert curation in code tours. Our design is grounded in requirements derived from 20+ meetings, surveys, and interviews across a year-long industry partnership with Beko. Supporting features include Voice-to-Tour capture, comprehension quizzes, podcasts, and a dashboard. We deployed Lacy on Beko's production environment and conducted a controlled study on a legacy finance system (30K+ LOC). Learners using expert-guided tours achieved 83% quiz scores versus 57% for AI-only tours, preferred tours over traditional self-study, and reported they would need fewer expert consultations. Experts found tour creation less burdensome than live walkthroughs. Beko has since adopted Lacy for organizational onboarding, and we release our code and study instruments as a replication package.

翻译：每个软件组织都面临入职挑战：帮助新手驾驭复杂代码库、弥补文档不足、并理解非自创代码。专家走查是最有效的支持形式之一，但成本高昂、重复性强且难以规模化。我们提出Lacy，一种混合人机入职系统，以可复用的代码导览来捕获专家指导——据我们所知，这是首个将AI生成内容与专家策展相结合的代码导览混合方法。我们的设计基于与Beko长达一年的行业合作中通过20余次会议、调查和访谈提炼的需求。支持功能包括语音转导览捕获、理解测验、播客和仪表盘。我们将Lacy部署于Beko的生产环境，并在一个遗留金融系统（3万+行代码）上开展了对照研究。使用专家指导导览的学习者得分83%，而纯AI导览仅57%；学习者更偏好导览而非传统自学，并表示能减少专家咨询次数。专家认为导览创建比实时走查负担更轻。Beko已采用Lacy进行组织级入职，我们同时发布代码与研究工具作为可复现包。