Spec-driven Development: How AI Changes Everything (And Nothing)

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1. Spec-driven Development Simon Martinelli

2. None

3. About Me • 30 years in Software Engineering • 25

   years with Java • Self-employed since 2009 • Teaching at two Universities • Co-lead Berne, JUG Switzerland

4. AI Native Development • Spec-Centric Development • Clear intent/specs guide

   AI to generate meaningful code • Context-Aware Development • AI agents understand full codebase context • Agent Experience AX • Autonomous AI tasks enhancing developer throughput https://ainativedev.io

5. Spec-driven Development (SDD) • Start with the specification, not the

   code • Specifications • Define the intended behavior of the system • Serve as shared contract between business and development • Are the single source of truth • Reduce guesswork and improve quality

6. Caution: AI Is Not a Compiler • AI code generation

   isn't a compiler - it's an assistant! • Many developers expect AI to work like a compiler • Precise input → perfect output • But that's not how it works • It’s not comparable to Model-Driven Development • AI is non-deterministic and makes mistakes • You are responsible for the output!

7. SDD in Pratice • Process • AI Unified Process AIUP

   https://unifiedprocess.ai • Tools • AIUP Claude Code Plugin https://unifiedprocess.ai/tools.html • Amazon Kiro https://kiro.dev • GitHub Spec Kit https://github.com/github/spec-kit • BMad https://github.com/bmad-code-org • ... and others

8. Why Use Cases? • Complete context • One place for

   goal, flows, and exceptions • Structured for AI • Clear input for generation and automation • Built-in testability • Tests define done and protect behavior • Natural unit of work • One use case drives one implementation cycle • Specification as source of truth • Code and tests are derived from it

9. Greenfield Workflow

10. Brownfield Workflow

11. https://github.com/ simasch/aiup-petclinic

12. Guidelines and Guardrails • Guidelines define rules • Standards, architecture,

    testing • Skills capture repeatable tasks • Implementation, testing, refactoring, reviews • MCP connects tools and context • Documentation, code examples, quality checks • Together they create guardrails • Human review stays essential

13. Impact on the Architecture • Modular architecture reduces the context

    size • Self-contained Systems • Microservices • Single ecosystem simplifies guardrails • Full-stack frameworks

14. Conclusion • Specs help to • Reduce non-determinism • Make

    development sustainable • It accelerates development, but you must: • Review, understand, and test the output • Know your architecture and domain

15. Thank you! • Web martinelli.ch • EMail [email protected] • Bluesky

    @martinelli.ch • X/Twitter @simas_ch • LinkedIn https://linkedin.com/in/ simonmartinelli