Data & semantics
Give agents durable facts, portable records, and shared meaning.
A REFERENCE ARCHITECTURE FOR COMPOSABLE AI
Build agentic systems from open data foundations, model choice, interchangeable harnesses, and portable standards—without surrendering the seams.
DEFINITION / 00
An open agentic platform is an architecture in which data, models, execution, and interoperability remain independently understandable and replaceable. “Open” may describe source, weights, formats, or interfaces. A trustworthy architecture labels the difference instead of flattening it.
ARCHITECTURE / 01–04
Each layer answers a different question. Together they turn model capability into durable, governable work.
Give agents durable facts, portable records, and shared meaning.
Choose models by task, policy, economics, and deployment needs.
Turn intent into governed work with interchangeable runtimes.
Make skills, context, profiles, and graphs portable across tools.
THE OPENNESS TEST / 05
A pile of open-source parts can still produce a closed architecture. Test the relationships as carefully as the licenses.
Can one component be swapped without rebuilding the system?
Can a builder understand what runs and why?
Can identity, skills, context, and work move?
Are authority and approval requirements explicit?
Do agents share durable data and semantic meaning?
Can people reconstruct decisions and outcomes?
A PRACTICAL PATH / 06
Start with durable context. Add intelligence and execution only after control boundaries are clear.
Choose open formats, a catalog, and a semantic layer that agents and people can share.
Express identity, skills, tools, workflows, policy, and approval points in portable forms.
Select models, routers, brokers, and harnesses according to the work—not brand gravity.
Retain evidence, evaluate outcomes, and replace components as requirements change.