Agenda
Morning: Foundations & first spec
- Why vibe coding fails: hallucinations, regressions, corrupted tests
- AI coding workflows: inline, agentic, spec-driven, dark factory
- SDD principle: spec as single source of truth, separating intent from implementation
- Business analysis for LLMs: Mermaid state machines, decision tables, BDD, invariants
- Exercise 1: Prompt a complex feature vaguely — feel the pain point
- Exercise 2: Turn the same feature into a full spec with data models, state machine and definition of done
Afternoon: Agentic engineering, architecture & strategy
- Four disciplines: prompt, context, intent and spec engineering
- AI architecture constraints: context limits, SDR principles, vertical slices, SCS
- Green-field vs. brown-field: strangler fig, discovery before mutation, zero-trust generation
- Exercise 3: Spec + agent → plan before code → review
- Exercise 4: Refactor code from Exercise 3 according to SDR principles
- Exercise 5: Dark Factory — hand spec to a fresh agent, let it implement autonomously
Method
Five exercise blocks build on each other: the feature from Exercise 1 runs through to the Dark Factory simulation in Exercise 5. All exercises can be done with your own project.
Prerequisites: Experience in software development. Familiarity with an AI coding assistant is an advantage.