The semantic substrate for cross-domain composition
The Problem
Domain Fragmentation Prevents Composition
Modern software development is siloed across incompatible representations:
Audio DSL → [export] → CAD Tool → [export] → UI Framework → [export] → ...
Each domain has its own:
- Data formats - Binary blobs, XML, JSON, proprietary formats
- Type systems - Python types ≠ MLIR types ≠ CAD geometry types
- Validation rules - Domain-specific constraints don't transfer
- Compilation targets - C++, LLVM, JavaScript, hardware descriptors
Real-world pain:
- Audio → CAD: Design guitar body acoustics in Morphogen → Can't generate 3D model automatically
- CAD → UI: Parametric design in TiaCAD → Can't generate responsive UI controls for parameters
- AI → Provenance → UI: Track model training pipeline → Can't embed trust metadata in UI components
- Software → Hardware: Design analog effect pedal in code → Can't generate module configuration for physical build
Result: No composition, no reuse, massive integration overhead. Professional workflows require 3-5 tool chains with manual export/import/translate cycles.
The Innovation
ONE universal semantic intermediate representation (IR) for ALL computational domains.
Pantheon enables seamless composition across traditionally siloed domains:
- Audio synthesis (Morphogen)
- Parametric CAD (TiaCAD)
- Process provenance (GenesisGraph)
- UI/Frontend (SUP)
- Analog computing (Philbrick)
- Multi-agent systems (Agent Ether*)
The Architecture: Three-Layer Model
Domain-Specific Frontends
┌─────────┬──────────┬───────────┬─────────┬──────────┐
│Morphogen│ TiaCAD │GenesisGraph│ SUP │Philbrick │
└────┬────┴────┬─────┴─────┬─────┴────┬────┴────┬─────┘
│ │ │ │ │
└─────────┴───────────┴──────────┴─────────┘
▼
┌───────────────────────┐
│ PANTHEON SEMANTIC IR │
│ • Typed graph nodes │
│ • Semantic edges │
│ • Rich metadata │
│ • Domain constraints │
│ • Provenance │
└───────────┬───────────┘
▼
┌─────────┬────────┴─────┬──────────┬─────────┐
│ MLIR │ CadQuery │ React │ Hardware│
└─────────┴──────────────┴──────────┴─────────┘
Domain-Specific Backends
One IR. Multiple frontends. Multiple backends. Infinite composition.
Core Innovations
1. Semantic Types (Not Just Shapes)
# Not just "f32" - semantic meaning with physical units
data_type: Stream<f32, 1D, audio>
sample_rate: {value: 48000, unit: Hz}
frequency: {value: 440, unit: Hz}
temperature: {value: 300, unit: K}
2. Semantic Time (Domain-Specific, Not Universal)
- Audio: samples (48kHz)
- Music: beats/measures (tempo-relative)
- Animation: frames (24fps, 60fps)
- Hardware: cycles (clock-dependent)
- Logical time > wall-clock time - each domain defines its own causal horizon and resolution
3. Universal Node Abstraction
@dataclass
class PantheonNode:
id: str # Unique identifier
type: NodeType # operator, entity, component, module
domain: str # Source domain
semantics: NodeSemantics # Intent, category, constraints
parameters: dict[str, Parameter] # Parameters with units
metadata: dict[str, Any] # Domain-specific metadata
4. Validation Framework
- Type checking (semantic types, not just shapes)
- Constraint validation (range, dimensionality, domain rules)
- Dependency resolution (node ordering, data flow)
- Safety checks (prevent invalid cross-domain connections)
5. Provenance-Aware by Design
metadata:
provenance:
source_file: guitar_body.kairo
git_commit: abc123...
generator_version: morphogen-0.11.0
parent_documents: [resonance_sim.pantheon.yaml]
Quick Example: Physics-Informed CAD
Scenario: Simulate guitar body resonance → Generate optimal 3D geometry
Step 1: Morphogen simulates acoustics
# resonance_field.pantheon.yaml (output from Morphogen)
version: pantheon-1.0
metadata:
domain: audio
creator: morphogen-dsl-v0.11
timestamp: 2025-11-28T00:00:00Z
nodes:
- id: guitar_body_resonance
type: operator
domain: audio
semantics:
intent: "Simulate guitar body resonant modes"
operator: modal_synthesis
parameters:
fundamental: {value: 110, unit: Hz} # Low E string
modes: [110, 220, 330, 440] # Harmonic series
outputs:
resonance_field: Field3D<f32 [Pa]> # Pressure field in 3D space
Step 2: TiaCAD reads Pantheon IR, generates geometry
from tiacad import CADWorkflow
from pantheon import PantheonGraph
# Load Morphogen's resonance simulation
resonance = PantheonGraph.from_yaml("resonance_field.pantheon.yaml")
# TiaCAD adapter reads Pantheon IR
workflow = CADWorkflow.from_pantheon(resonance)
# Use field data to guide body thickness variation
# (thicker where resonance needs damping, thinner where it needs amplification)
body_3d = workflow.generate_geometry(
thickness_field=resonance.get_output("resonance_field"),
material="spruce",
target_mass=1.5 # kg
)
# Export to 3D model
body_3d.save("guitar_body.3mf")
This is impossible in existing tools. You'd need:
- Morphogen or COMSOL (acoustic simulation) → Manual export
- Python scripts to parse simulation data → Brittle translation
- TiaCAD or SolidWorks (CAD modeling) → Manual parameter entry
- Hours of iteration per design change
Pantheon does it automatically. One semantic IR connects both domains.
Status & Adoption
Current Version: v0.1.0-alpha (Design Phase with Proof-of-Concept)
Production Metrics:
- ✅ Morphogen adapter complete - Bidirectional translation working
- ✅ Round-trip fidelity tests passing - Morphogen → Pantheon → Morphogen preserves semantics
- ✅ Semantic time specification integrated across adapters
- ✅ Schema definition complete (nodes, edges, types, validation, metadata)
- 🔄 Python reference implementation in progress (pantheon-core)
- 🔄 Prism adapter (analytics) design complete (Week 7-10 roadmap)
Novel Research Contributions:
-
Universal Semantic Graph Representation
- Typed graph nodes with domain semantics (not just structural graphs)
- Semantic edges carrying types, units, constraints, rates
- Human-readable YAML/JSON (not binary blobs)
- Provenance-aware by design (track "how this was created") -
Semantic Time Model
- Time is domain-specific, not universal
- Audio (samples @ 48kHz) ≠ Music (beats @ tempo) ≠ Animation (frames @ 60fps)
- Logical time > wall-clock time
- Each domain defines its own causal horizon and resolution -
Cross-Domain Type System
- Semantic types: meaning + constraints, not just shapes
- Physical units enforced (Hz, dB, m, kg, K, etc.)
- Domain-specific constraints (range, dimensionality, rates)
- Type-safe connections between domains (field → agent force, geometry → audio impulse) -
Validation Framework with Domain Constraints
- Type checking (semantic types)
- Constraint validation (range checks, unit compatibility)
- Dependency resolution (node ordering)
- Safety checks (prevent invalid cross-domain connections)
What This Unlocks:
- Cross-domain workflows - Physics simulation directly drives CAD geometry
- Reusable components - Audio operators compile to both software and hardware
- AI-friendly IR - LLMs can read, write, and reason about Pantheon graphs
- Multi-backend compilation - One design → MLIR, CadQuery, React, firmware
v1.0 Release Timeline: Active development
- TiaCAD adapter implementation
- GenesisGraph adapter (provenance integration)
- SUP adapter (UI component generation)
- Philbrick adapter (software/hardware co-design)
Technical Deep Dive
Full Documentation:
- Pantheon GitHub Repository
- Architecture Guide
- Schema Specification
- Morphogen Adapter - Bidirectional translation working ✅
- Roadmap - Detailed development timeline
Example Gallery:
- Physics-Informed CAD - Morphogen → TiaCAD
- Provenance-Aware UI - GenesisGraph → SUP
- Hardware/Software Co-Design - Morphogen ↔ Philbrick
Getting Started:
git clone https://github.com/Semantic-Infrastructure-Lab/pantheon.git
cd pantheon/adapters/morphogen
python -m pytest tests/ # See round-trip fidelity tests
Part of SIL's Semantic OS Vision
Pantheon's Role in the 7-Layer Semantic OS:
- Layer 3 (Composition): Universal semantic graph representation
- Typed graphs enable cross-domain composition
- Semantic edges carry domain-specific metadata
-
Provenance tracks transformations across layers
-
Layer 5 (Intent): Validation framework with constraint solving
- Type checking enforces semantic correctness
- Constraint validation (range, units, dependencies)
- Safety checks prevent invalid compositions
Composes With:
- Morphogen (Layer 1/4): ✅ PROVEN - Bidirectional adapter complete, round-trip fidelity tests passing
- Audio synthesis and physics simulation → Pantheon IR
- Proves universal IR pattern works with production code
- TiaCAD (Layer 2): Parametric CAD modeling → Pantheon IR (planned)
- Geometry operations, constraints, assemblies
-
Physics-informed design (Morphogen → Pantheon → TiaCAD)
-
GenesisGraph (Layer 2/3): Process provenance → Pantheon IR (planned)
- Provenance graphs become Pantheon nodes
-
Enable "show your work" for cross-domain workflows
-
SUP (Layer 3): UI component compilation → Pantheon IR (planned)
- Semantic UI primitives
-
Provenance-aware UI (GenesisGraph → Pantheon → SUP)
-
Philbrick (Layer 0): Hardware substrate → Pantheon IR (planned)
- Software/hardware co-design
-
Morphogen ↔ Pantheon ↔ Philbrick compilation
-
Agent Ether (Layer 6): Multi-agent coordination → Pantheon IR (planned)
- Agent behaviors as Pantheon graphs
- Enable cross-domain agent composition
Architectural Principle: One IR to Unify Them All
Pantheon proves that semantic-first design enables composition across traditionally incompatible domains. When domains share a universal IR, professional workflows transform from "export/import hell" to "compose naturally."
The Key Insight:
Most systems treat composition as an afterthought (add glue code later). Pantheon makes composition the foundation:
- Semantic types prevent dimensional errors
- Validation framework catches incompatible connections
- Provenance tracks transformations end-to-end
- Multi-backend compilation enables "one source, many targets"
This solves the fragmentation that forces professional workflows to span 3-5 incompatible tool chains.
Impact: Real-World Workflows Transformed
Before Pantheon:
- Audio design (Morphogen) → Export WAV → Import to CAD (manual parameter entry) → Iterate (hours per cycle)
- CAD model (TiaCAD) → Export STEP → UI builder (manual control creation) → No parameter linking
- AI pipeline (Python) → Manual provenance logging → UI (React) → Separate trust indicators
With Pantheon:
- Morphogen → Pantheon IR → TiaCAD (automatic geometry generation from acoustics)
- TiaCAD → Pantheon IR → SUP (automatic UI controls for parameters)
- GenesisGraph → Pantheon IR → SUP (provenance-aware UI components)
- Morphogen → Pantheon IR → Philbrick (software simulation → hardware build)
Use Cases Enabled:
-
Physics-Informed Design
- Acoustic simulation drives CAD geometry (guitar bodies, speaker enclosures)
- Thermal analysis optimizes heat sink topology
- Fluid dynamics guides aerodynamic shape -
AI-Driven CAD
- Generative design with provenance tracking
- Parametric models with AI-suggested optimizations
- Explainable geometry (show why each parameter exists) -
Hardware/Software Co-Design
- Design analog circuit in software → Generate hardware module config
- Validate software simulation against physical prototype
- Bridge digital/analog computing (Morphogen ↔ Philbrick) -
Provenance-Aware Applications
- UI components display trust metadata automatically
- Audit trails embedded in outputs
- Reproducible workflows (capture entire pipeline in Pantheon IR)
Adoption Path (v1.0 Goals):
- 5+ domain adapters production-ready (Morphogen ✅, TiaCAD, GenesisGraph, SUP, Philbrick)
- 10+ cross-domain example workflows
- Industry adoption in audio production, CAD/CAM, AI/ML tooling
Version: 0.1.0-alpha → 1.0 (Active Development)
License: Apache 2.0
Status: Design phase with proof-of-concept (Morphogen adapter working)
Learn More:
- GitHub Repository
- Architecture Documentation
- Roadmap