AI-driven Domain Design Training
Level
IntermediateDuration
18h / 3 daysDate
Individually arrangedPrice
Individually arrangedAI-driven Domain Design Training
Practical training for technical teams that want to use generative AI to support domain analysis, Domain-Driven Design modeling, and work with domain code. Participants move from requirements analysis and discovering Bounded Contexts, through Event Storming and modeling, to implementation, testing, refactoring, and code review using AI tools. The training focuses on human work supported by AI, rather than autonomous system design. Particular emphasis is placed on validating model outputs, testability, quality control, LLM limitations, and the safe use of data and code in AI tools.
Who is this training for?
Developers with a minimum of 2 years of experience in object-oriented programming, familiar with the basics of DDD and design patterns-
Software architects working with domain modeling and system boundaries
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Senior developers responsible for the quality of the domain model and code
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Tech leads making design and architectural decisions
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Technical professionals using or planning to use AI tools in software analysis, design, and implementation
What will you learn during the training?
- Analyzing business descriptions with the help of AI and identifying concepts, rules, and ambiguities requiring verification
- Identifying and validating Bounded Contexts against business responsibilities
- AI-supported Event Storming and modeling aggregates, entities, Value Objects, and domain events
- Implementing and refactoring domain code using AI while maintaining control over architectural decisions
- Designing unit tests for business rules, invariants, and edge cases
- AI-supported code review and assessing code compliance with the domain model
- Validating AI outputs for correctness, hallucinations, data security, code quality, and the need for human oversight
Training program
Day 1
Module 1: Fundamentals of AI-driven Domain Design
- Fundamentals of AI-driven development and the role of humans in domain decisions
- AI tools for analyzing business requirements and working with context
- Analyzing business requirements with AI – domain concepts, rules, and ambiguities
Module 2: Domain Analysis and Modeling with AI
- Bounded Contexts – heuristics for identification with the help of AI
- AI-supported Event Storming
- Domain models with AI – aggregates, entities, Value Objects, and business rules
Day 2
Module 3: Implementing the Domain Model with AI
- Aggregates and domain entities with AI – responsibilities, invariants, and boundaries
- Refactoring domain code with AI
- Domain unit tests with AI – business rules, edge cases, and validation
Module 4: Code Quality and Documentation with AI
- Documenting the model and architectural decisions with AI
- AI-supported code review – quality criteria, security, and error identification
- Complete domain with AI – model, code, and tests
Day 3
Module 5: Advanced DDD Patterns Supported by AI
- Domain events with AI – semantics, contracts, and responsibility boundaries
- DDD patterns supported by AI – selection and implementation validation
- Integration patterns with AI – synchronous and asynchronous communication between contexts
Module 6: Quality, Risks, and AI-driven Development Practice
- Performance of AI-generated code – profiling and acceptance criteria
- Best practices and risks of AI-driven development – hallucinations, data privacy, security, auditability, and human oversight
- Complete project using AI – model, code, tests, and quality review
