BMAD-METHOD/docs/method/design-space-guide.md

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Design Space — The Design Consciousness

By: Whiteport Collective (2026)


The Core Idea

A design system is a projection — tokens, components, patterns. It's the cogs.

The Design Space IS the consciousness — the living environment where design happens across products, accumulating decisions, experiments, and outcomes over time.

Where a design system says "use 8px spacing," the Design Space remembers why: the failed experiment with 4px, the client feedback that led to the change, the A/B test that confirmed it.


Architecture

Dual Embedding Model

Every entry in the Design Space can have two independent representations:

Embedding What It Captures Technology
Semantic (1536d) What it means — descriptions, reasoning, context OpenRouter / text-embedding-3-small
Visual (1024d) What it looks like — colors, layout, typography, imagery Voyage AI / voyage-multimodal-3

Semantic embeddings capture conceptual similarity: "navy hero with centered text" matches "dark hero with centered heading." Visual embeddings capture aesthetic similarity: two designs can mean different things but look the same.

Together they detect patterns that either alone would miss.

Memory Categories

Category What Gets Captured
inspiration Visual references, competitor patterns, moodboards
failed_experiment What didn't work and why
successful_pattern Validated solutions worth reusing
component_experience How components behave in real use
design_system_evolution Token changes with reasoning
client_feedback Designer reactions, preference patterns
competitive_intelligence How competitors solve problems
methodology Process improvements, workflow discoveries
agent_experience Agent collaboration learnings
reference External resources worth remembering
general Anything that doesn't fit above

Pattern Types

Every visual capture is tagged with its role in the design journey:

Symbol Type Meaning
baseline Inherited starting point
inspiration External reference
Δ delta What changed
rejected Designer didn't like it
approved Designer liked it
conditional Works in some contexts

The Design Feedback Loop

The most powerful capability. When the designer works with Freya:

  1. Freya creates a design
  2. Designer reviews and requests a change
  3. Freya captures BEFORE (semantic + visual, tagged rejected)
  4. Freya asks WHY — naturally, not as interrogation
  5. Designer explains (or Freya infers from the change)
  6. Freya applies the change
  7. Freya captures AFTER (semantic + visual, tagged approved)
  8. Both saved as a linked pair (shared pair_id)
  9. Patterns emerge: "Designer consistently prefers X over Y"
  10. Future designs are pre-checked against known rejections

The Learning Curve

Cold start (0-10 pairs): Individual preferences. "Likes light headings."

Accumulation (10-50 pairs): Clusters form. "Prefers understated elegance."

Taste profile (50+ pairs): Agent predicts preferences before asking.

Design DNA (100+ pairs): New agents inherit the designer's aesthetic sensibility from day one.

Red Flag Detection

Before presenting ANY new design, the agent searches for matches against rejected patterns:

  • Semantic red flag: Description matches previously rejected descriptions
  • Visual red flag: Screenshot looks like previously rejected screenshots
  • If either triggers → adjust before showing the designer

How WDS Uses It

Phase Agent Design Space Interaction
0 Alignment Saga Search for similar past projects
1 Product Brief Saga Search competitive intelligence, capture business insights
2 Trigger Map Saga Search user psychology patterns, capture trigger discoveries
3 Scenarios Both Search similar flows, capture scenario decisions
4 UX Design Freya Search + visual search, capture decisions, run feedback loop
5 Agentic Dev Freya Search agent experiences, capture collaboration insights
6 Assets Freya Search generation learnings, capture prompt patterns
7 Design System Freya Search evolution history, capture token decisions
8 Evolution Freya Search everything, capture product evolution insights

Core Principles

Craft follows the designer. Knowledge accumulates with the person who did the work, not the client who paid for it.

Auto-capture by default. Agents capture insights as they work — the designer never has to ask.

Search before you create. Always check what exists before starting new work.

The feedback loop is not an interruption — it is the learning.


Technical Foundation

  • Database: Supabase with pgvector (eu-north-1, Stockholm)
  • MCP Server: design-space-mcp with 8 tools
  • Semantic: OpenRouter (text-embedding-3-small, 1536d)
  • Visual: Voyage AI (voyage-multimodal-3, 1024d)