Core Concepts

Blocks treats domain concepts as first-class, executable artifacts — inspired by Cube.dev, Malloy, and PDDL.

The Three Pillars

Entities

Entities are the "things" in your domain.

domain:
  entities:
    user:
      fields: [id, name, email, created_at]
    resume:
      fields: [basics, work, education, skills]

Reference entities using entity.<name>:

blocks:
  my_block:
    inputs:
      - name: user
        type: entity.user

Signals

Signals are domain-specific concepts to extract or calculate.

domain:
  signals:
    engagement:
      description: "How engaged is the user?"
      extraction_hint: "Based on activity frequency and recency"
    readability:
      description: "Clear visual hierarchy and typography"

Signals guide AI validation and give semantic meaning to data.

Measures

Measures are constraints on output values.

domain:
  measures:
    score_0_1:
      constraints:
        - "Value must be between 0 and 1."
        - "Higher values indicate stronger signal."
    semantic_html:
      constraints:
        - "Use semantic tags (header, main, section)"
        - "Proper heading hierarchy (h1 → h2 → h3)"

Reference measures in outputs:

blocks:
  my_block:
    outputs:
      - name: score
        measures: [score_0_1]

Why Domain Modeling Matters

Without domain modeling:

Developers hallucinate structures
Conventions drift over time
Semantic meaning is lost in code
No consistency across blocks

With domain modeling:

✅ Explicit semantics
✅ Drift detection when changes occur
✅ Evolutionary design through negotiation
✅ Humans and AI agents maintain alignment through validation

Next Steps

Entities

Learn about domain entities in depth

Signals

Understand domain signals

Measures

Define output constraints

Philosophy

Guide development with design principles