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Vision Driven Design

License: MIT 8 Phases Version 1.5.3 7 Bidirectional Gates 113 Verification Checks OpenCode Skill GitHub stars Last commit Built with VDD

From vision to verified impact — an AI-native, fully autonomous software development methodology.

VDD extends and absorbs Spec-Driven Development (SDD). Provide a human vision statement. The AI autonomously researches, audits your codebase, generates specs and plans, implements, and validates — with bi-directional verification at every junction to ensure nothing is missed or invented.


graph LR
    V[1. Vision<br/>Human Input] -->|<-->| S[2. Strategy<br/>AI Research]
    S -->|<-->| T[3. Tactics<br/>AI Audit]
    T -->|<-->| SP[4. Specs<br/>SDD]
    SP -->|<-->| PL[5. Plan]
    PL -->|<-->| TK[6. Tasks]
    TK -->|<-->| IM[7. Implement]
    IM -->|<-->| VS[8. Validate<br/>Impact Verified]

    style V fill:#4CAF50,color:#fff
    style S fill:#2196F3,color:#fff
    style T fill:#FF9800,color:#fff
    style SP fill:#9C27B0,color:#fff
    style VS fill:#4CAF50,color:#fff
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Who Is This For?

  • Product teams who want AI to drive development from a business goal, not a spec document
  • Solo developers who have a vision but lack the bandwidth for research, planning, and specs
  • Open source maintainers who need auditable traceability from vision to code
  • Webapp / data / ETL / infrastructure builders whose projects span multiple technical domains
  • Anyone frustrated with SDD because it starts at the spec level and doesn't connect to real-world impact

Table of Contents


Quick Start

# One-line install (auto-detects your agent and project)
curl -sSL https://raw.githubusercontent.com/simonplmak-cloud/vision-driven-design/main/scripts/install.sh | bash

Or manually:

Then in your project:

/vdd:init                          # Generate project constitution (once)
/vdd:vision "your vision here"     # The only human input required

The AI takes over from here — researching markets, auditing your codebase, generating specs, planning architecture, breaking down tasks, implementing feature by feature, and validating impact — all with self-gating at 7 bi-directional verification junctions.

📖 Full Tutorial → — 30-minute walkthrough building a real project with VDD.

# Want human gates? Add to constitution.md:
## VDD Mode: gated

How It Works

VDD follows Goldratt's recursive Strategy-Tactic decomposition: every phase is simultaneously the Tactic for its parent and the Strategy for its child.

Phase S&T Role Output
1. Vision L1 Strategy: What impact? vision.md — Impact model, success metrics
2. Strategy L1 Tactic → L2 Strategy strategy.md — Research, pillars, risk register
3. Tactics L2 Tactic → L3 Strategy tactics.md — Codebase audit, action items
4. Specs L3 Tactic → L4 Strategy spec.md — MoSCoW acceptance criteria
5. Plan L4 Tactic → L5 Strategy plan.md, data-model.md, contracts/
6. Tasks L5 Tactic → L6 Strategy tasks.md — Test-first atomic tasks
7. Implement L6 Tactic → L7 Strategy Code — Per-task commits with full traceability
8. Validate L7 Tactic — Did it work? impact-report.md — Drift + impact verification

7 bi-directional gates verify both directions at every junction (113 total checks). Each gate also validates 4 S&T assumptions: Necessity, Achievability, Sufficiency, Warnings.

Every code commit traces back to the original vision statement through the full chain:

V-001 → S-002 → T-003 → SP-004 → PL-005 → TK-006 → commit

What Makes VDD Different

Feature Traditional SDD Vision Driven Design
Starting point Spec document Human vision statement
Research Not included 5 parallel research subagents (market, competitive, tech, impact, domain)
Codebase awareness Not included Full repository audit before spec generation
Traceability Spec → Code Vision → Strategy → Tactics → Spec → Plan → Code → Impact
Verification Forward only Bi-directional at every level (7 gates, 113 checks)
Impact verification Not included Leading + lagging metrics validated against vision
Domain awareness Generic 6 domain primers (4 conditional + 2 unconditional)
Autonomy Per-phase human gates Full-auto mode — human provides vision only

Commands

Command What it does
/vdd:init Generate project constitution
/vdd:vision "..." Expand freeform vision into structured impact model
/vdd:strategize Research market, competitors, technology → strategic pillars
/vdd:tactics Audit codebase → gap analysis → prioritized action items
/vdd:specify <ID | "desc"> Generate acceptance criteria from action item or freeform
/vdd:clarify <feature> Standalone clarification pass on a spec
/vdd:plan <feature> Technical architecture, data model, API contracts
/vdd:tasks <feature> Test-first task breakdown with dependencies
/vdd:next-task <feature> Extract next uncompleted task
/vdd:implement <ID> Execute single task, verify, commit
/vdd:validate Full-chain traceability matrix + drift detection + impact report
/vdd:trace Generate bidirectional traceability matrix
/vdd:analyze Cross-artifact consistency and conflict analysis
/vdd:amend Cascade requirement change through full chain

Installation

OpenCode

git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  ~/.config/opencode/skills/vision-driven-design/

Claude Code

git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  ~/.claude/skills/vision-driven-design/

Cursor

git clone https://github.com/simonplmak-cloud/vision-driven-design.git \
  .cursor/skills/vision-driven-design/

Domains Covered

VDD loads domain-specific research patterns during the Strategy phase based on your vision:

Domain What it covers
WebApp UX, accessibility (WCAG 2.2), performance budgets, framework evaluation
Data Storage Schema design, indexing strategy, data governance, ACID vs eventual
ETL Pipeline architecture, data quality frameworks, batch vs streaming
Infrastructure CI/CD, observability, security, scaling, disaster recovery
Human Factors Behavioral economics, cognitive load, habit formation, accessibility cognition
Verification Toolchain Playwright, Browserless, Sentry, CI/CD quality pipeline integration

Each primer also includes impact verification patterns — how to prove real-world impact in that domain. human-factors.md and verification-toolchain.md are loaded unconditionally for every project.


Documentation

All reference docs live in references/:

File Contents
workflow-phases.md Step-by-step for all 8 phases (authoritative)
artifact-templates.md Copy-paste templates for all 11 artifacts
prompt-patterns.md AI prompts for generation + bidirectional gate verification
quality-gates.md 7 gates with 113 checks + CI/CD integration
ai-agent-patterns.md Multi-agent orchestration and auto-mode execution
anti-patterns.md 24 failure modes and fixes
traceability-matrix.md RTM format + automated generation
quick-reference.md One-page cheat sheet

Guides


Repository Structure

├── SKILL.md                         # Entry point — loaded by OpenCode
├── AGENTS.md                        # Instructions for AI agents working on this repo
├── README.md                        # This file
├── constitution.md                  # This repo's own constitution (dogfooded)
├── CHANGELOG.md                     # Versioned change history
├── CONTRIBUTING.md                  # How to contribute
├── LICENSE.md                       # MIT
├── domain-primers/                  # Domain research patterns (loaded during Strategy)
│   ├── webapp.md
│   ├── data-storage.md
│   ├── etl.md
│   ├── infrastructure.md
│   ├── human-factors.md             # Behavioral economics, cognitive load, habit formation
│   └── verification-toolchain.md    # Playwright, Browserless, Sentry, CI/CD pipeline
├── references/                      # All reference documentation
│   ├── INDEX.md                     # Navigation map
│   ├── quick-reference.md           # 1-page cheat sheet
│   ├── workflow-phases.md           # 8 phases step-by-step (authoritative)
│   ├── artifact-templates.md        # 11 copy-paste templates (authoritative)
│   ├── prompt-patterns.md           # All prompts + bidirectional gate verification
│   ├── quality-gates.md             # 7 gates with 113 checks
│   ├── ai-agent-patterns.md         # Multi-agent orchestration and auto-mode
│   ├── anti-patterns.md             # 24 failure modes and fixes
│   └── traceability-matrix.md       # RTM format + CI/CD automation
├── scripts/                         # Installer and helper scripts
│   ├── install.sh                   # One-line installer
│   ├── vdd-agent-setup.sh           # Multi-agent config generator
│   ├── vdd-detect.sh                # Project convention auto-detector
│   └── vdd-substance-audit.sh       # Low-substance artifact detection
└── .github/                         # GitHub-specific config
    ├── CODEOWNERS
    ├── ISSUE_TEMPLATE/
    └── workflows/

Credits

Built on:

  • Goldratt's Strategy-and-Tactic Tree — recursive decomposition at every phase
  • Impact Mapping (Gojko Adzic) — goal → actors → impacts → deliverables
  • GitHub Spec Kit — spec-driven development with AI agents
  • NASA Systems Engineering — bidirectional traceability and verification chains
  • CMMI Requirements Management — bidirectional traceability of requirements

License

MIT — see LICENSE.md

About

Bi-directional traceability for AI-assisted development — prove every commit traces to the business goal that authorised it. 8-phase chain, 7 gates, 113 checks. Skill for Claude Code, Cursor and OpenCode.

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