AI Assistance for Architectural Decision Making: Domain-Driven Context and Prompt Engineering
Journal
Workshop on Intelligent & Data-driven Engineering for Software Architecture (IDEA-ARCH)
Type
conference paper
Date Issued
2026-10
Author(s)
Abstract
Generative Artificial Intelligence (AI) is receiving a lot of focus in research and practice at present; positions vary from euphoria to "just another tool" to skepticism. Software architecture analysis, synthesis, and evaluation offer many opportunities for AI, e.g., support for knowledge-intensive tasks such as making and recording architectural decisions. It is not yet fully understood how architects can be assisted by AI effectively and efficiently: AI services have to be supervised via input specifications and output validation, requiring architecting skills and application domain expertise. In this paper, we identify architecturally significant requirements to drive the design of a future ecosystem of AI-Assisted Decision Assistance tools (AID). We apply Domain-Driven Design (DDD) to establish a logical component architecture for AID that leverages model-driven knowledge management concepts to accelerate context and prompt/skills engineering and to guard response processing.
Language
English (United States)
Keywords
Architectural Knowledge Management
API Design
Domain-Driven Design
Generative AI
Model-Driven Software Engineering
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Springer
Pages
8
Event Title
Workshop on Intelligent & Data-driven Engineering for Software Architecture (IDEA-ARCH)
Event Location
Bolzano, Italy
Event Date
Sep 7, 2026
Subject(s)
Division(s)
File(s)![Vorschaubild]()
open.access
cris-layout.advanced-attachment.dc.title
2026___IDEA_Arch___ModelDrivenContextAndPromptEngineering.pdf
cris-layout.advanced-attachment.size
500.37 KB
cris-layout.advanced-attachment.format
Adobe PDF
cris-layout.advanced-attachment.checksum (MD5)
985cffbcf4d9b5e37991e68051361eb7