Targets are outputs
Harness-specific files become compilation targets rather than the permanent underlying source of truth.
Architecture
Rangoon is being designed around a structured intermediate representation that preserves agent capability meaning while adapters generate target-specific artifacts.
Product direction · In active development
A canonical representation can include identity, activation, instructions, inputs, outputs, tools, dependencies, resources, permissions, policies, compatibility, provenance, and tests.
Harness-specific files become compilation targets rather than the permanent underlying source of truth.
Imported assets can retain repository, file, revision, lines, detection method, confidence, user modifications, ancestry, generated targets, and deployment history.
A capability should retain the evidence needed to understand where it came from.
The architecture separates composition and management from LNSAT evaluation for consequential execution.
This architecture describes planned product direction rather than a stable public contract.
The future is open
Let’s build an AI ecosystem worth trusting.
