| name | aiase-sdd |
| description | Spec-Driven Development (SDD) — how to write specs before coding with AI, the dimensional ascension/descent workflow, and dialogue-to-spec-to-code pipeline. Load when the user asks about writing specs, requirements, AIASE course SDD, or before starting any AI-assisted coding task. |
Spec-Driven Development (SDD)
From AIASE 2026 (NCKU), Weeks 2–5. The core thesis: write the spec first; let the AI write the code from the spec.
Core Model: Dimensional Ascension & Descent
- Ascent (1D → 3D): Lift fragmented requirements into a comprehensive architectural blueprint — structured Markdown + Mermaid diagrams.
- Descent (3D → 1D): Translate that blueprint into executable code precisely, with minimal ambiguity.
A good diagram beats ten paragraphs. AI translates visual logic into precise code; it can't reliably infer intent from prose.
The Three-Layer Contract
Every SDD project has three layers:
-
System Prompt / AGENTS.md = Architectural Specification
- Role (capability boundary)
- Goal (success metric)
- Constraints (what's forbidden)
- Output Format (testable spec)
-
Tool Schema = API Contract
- Precise descriptions: when to use, when NOT to use
- Parameter validation: type, range, defaults
- Return format + explicit error cases
-
Eval Cases = Test Suite
- Golden dataset (hand-verified examples)
- Scoring: exact match, semantic match, or LLM-as-Judge
- Regression tests (new changes must not break passing cases)
Dialogue-to-Spec Pipeline (W5 Phase 1–5)
Phase 1: Dialogue → Requirements
Start with incomplete request. Claude asks clarifying questions.
Define: feature boundary, permission model, response format, error handling.
The dialogue IS the requirements process — no upfront spec needed.
Phase 2: Spec Document
Crystallize discussion into structured Markdown.
Version from v0.1 (endpoints) → v0.4 (MCP plans, Mermaid diagrams).
Each iteration adds one concern; never rewrite the previous version.
Phase 3: Security Review
Switch Claude to "information security expert" role.
Threat-model against the spec.
Produce security_check.md with 30+ actionable items.
Phase 4: Multi-Agent Team Design
Match agent roles to project phases and security concerns.
Write multiagent-plan.md describing each agent's mandate.
Phase 5: Execution
Upload spec + security checklist + agent plan as shared knowledge.
Team Lead coordinates; teammates resolve dependencies peer-to-peer.
Effective Prompt Structure
Every prompt to an AI needs four elements:
- Context — current program state
- Task — what to build/fix
- Constraints — forbidden libraries, required conditions
- Format — expected output structure
The Rolling Snowball Method
Build incrementally:
- MVP only
- Add one feature per iteration
- Verify each step before proceeding
This prevents cascading errors and keeps it obvious which change caused a problem.
Interaction Maturity Levels
| Level | Method | Typical User |
|---|
| Tier 1 | Unstructured natural language | Casual users |
| Tier 2 | Structured Markdown + constraints | Intermediate developers |
| Tier 3 | Full SDD + diagrams + multi-agent | Senior engineers directing AI teams |
Anti-Patterns
"Vibe Coding ≠ non-programmers writing programs. Vibe Coding = programmers who understand logic, accelerated by AI."
You must be able to:
- Verify AI outputs for logic errors
- Debug the generated code
- Catch hallucinated tool calls
See also: [[aiase-rpi]] for the Research-Plan-Implement workflow, [[aiase-harness]] for CLAUDE.md/AGENTS.md structure.
