Composability
AI Products must be designed for composability — the ability to integrate and interact with other AI Products, Data Products, or software services to form higher-order systems.
Composability transforms isolated products into ecosystem building blocks.
Why Composability Matters
- Scalability → Complex solutions emerge from smaller, modular products.
- Reusability → Products can be applied across multiple workflows and domains.
- Governance → Composable systems allow governance policies to be enforced at multiple levels.
- Innovation → New applications arise from creative combinations of existing products.
- Future-Proofing → Composable design adapts to new standards and emerging product types.
Composability Requirements
AI Products must declare:
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Composable Interfaces
- Clear input/output schemas (see Inputs & Outputs).
- APIs compatible with standardized protocols (see Interoperability & Standards).
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Dependency Declaration
- Which upstream or downstream products they can interact with.
- Optionality vs mandatory dependencies.
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Chaining & Orchestration
- Whether the product supports sequencing, parallelization, or agent-based orchestration.
- Workflow compatibility (e.g., Airflow, Prefect, Kubeflow, LangChain).
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Extension Mechanisms
- Plug-in architecture, adapters, or wrapper interfaces.
- Declared integration points for downstream customization.
Composability Patterns
- Pipelining → Sequential use of multiple AI Products (e.g., OCR → Summarizer → Classifier).
- Ensembling → Combining outputs of multiple AI Products for stronger results.
- Chaining → Multi-step reasoning or generation across specialized products.
- Agentic Composition → Agents coordinating multiple products autonomously.
Governance Integration
- Composability must align with Governance & Policy.
- Provenance and lineage must declare composable contexts (see Lineage & Provenance).
- Risks must be assessed at both product and system level.
Example
AI Product: Enterprise Chat Assistant
- Composable Interfaces: REST + GraphQL APIs, outputs JSON conversation objects.
- Dependencies:
- Upstream: Enterprise Knowledge Graph (Data Product).
- Downstream: Translation AI Product for multilingual support.
- Chaining & Orchestration: Supports orchestration via LangChain and BPMN workflows.
- Extension Mechanisms: Allows plug-ins for domain-specific FAQ modules.
Summary
- Composability enables AI Products to function as modular, reusable building blocks.
- Requires standardized interfaces, dependency declarations, orchestration compatibility, and extension mechanisms.
- Supports ecosystem-level innovation, governance, and future-proofing.
Principle: An AI Product without composability is an isolated artifact — valuable in itself, but unable to contribute to systemic intelligence.