arc42 has given us a precise and disciplined way to document software architecture — but AI systems behave fundamentally differently. They don’t stay static. They learn, drift, depend heavily on data quality, and make probabilistic decisions. Yet today, we still document them as if they were ordinary code components. And that’s where things break.
In real projects, we see the same recurring problems: invisible data dependencies, unclear assumptions, models no one can explain, domain language drifting away from training data, unpredictable deployments, missing ownership, and no architectural place to describe feedback loops, retraining logic, or drift mitigation. When these elements aren’t captured architecturally, AI systems become unmaintainable and impossible to govern.
arcAI42 introduces a small set of lightweight extensions to arc42 that make these learning systems architecturally visible. It adds a Data and Domain Context that describes data sources and meaning, a Model Context that explains model assumptions and provides transparency into model behavior, a Lifecycle & Feedback View that shows how a model evolves, and a Governance & Risk section that captures drift, bias, ownership, and mitigation strategies. It also clarifies how models are tested, deployed, monitored, and rolled back.
In essence, arcAI42 transforms AI from a black box into a first-class architectural element — giving architects and data scientists a shared language, and ensuring these systems remain explainable, traceable, and safe as they become part of everyday infrastructure.
Dr. Nikita Golovko is a seasoned Solution Architect with over 16 years of experience in designing scalable, secure, and cost-effective software architectures for industrial and business-critical systems. With a strong academic background and research in machine learning, he bridges the gap between advanced AI technologies and real-world applications on the shop floor. Nikita has led full project lifecycles—from requirements and architecture design to deployment—ensuring compliance with security and industry standards. He is known for translating business needs into robust architectures and aligning cross-functional teams. Passionate about innovation and sustainability, he focuses on applying AI, IoT, and edge computing to drive continuous improvement in industrial environments.
Auf der Veranstaltung werden Film- und Tonaufnahmen sowie Fotos gemacht, mit deren auch späteren Verwendung Sie sich durch den Besuch der Veranstaltung einverstanden erklären. Wenn Sie nicht fotografiert oder gefilmt werden möchten, können Sie direkt den/die FotografIn oder den/die Kameramann/-frau ansprechen.
Die Aufnahmen können im Internet, auf Social Media Kanälen sowie in Rundfunk-, TV-, und Printmedien (auch Büchern) veröffentlicht werden.
Die Verarbeitung erfolgt aufgrund des berechtigten Interesses der Verantwortlichen, die von ihr organisierte Veranstaltung bildlich zu dokumentieren und einer größeren Öffentlichkeit positiv darüber zu berichten
