A governed path from authoritative source to product decision.
A source-and-routing system for Apple and spatial development that distinguishes authority, experiments, and real build evidence before information reaches product work.
03 / proof surface
01 / The challenge
Start with the operating tension.
AI-assisted research can produce polished answers that are stale, weakly sourced, or inappropriate for a real build. Product teams need a way to know what is authoritative, what is experimental, and what has actually been verified.
02 / The approach
Shape the system around the constraint.
SOURCEHUB treats provenance and acceptance criteria as product infrastructure. Sources are graded, routed into project-specific action maps, and kept separate from build, simulator, device, and headset evidence.
03 / The working system
What exists.
- 01
Apple documentation, WWDC session, sample, and live-cache routing
- 02
Explicit source hierarchy and evidence tiers
- 03
Project-specific action maps and acceptance criteria
- 04
Bounded compute delegation with reviewed sources retaining authority
Capabilities demonstrated
Transferable judgment, shown in context.
04 / What the evidence supports
Proof on the page.
- A governed local source system, routing maps, evidence tiers, and acceptance rules exist.
- The workflow distinguishes documentation, experiment output, and build/simulator/device/headset receipts.
- A low-quality delegated path was rejected instead of being silently promoted into the knowledge base.
Claim boundary
Where the evidence stops.
- The knowledge corpus is not published and may include redistribution restrictions.
- No speed, accuracy, or delivery improvement is claimed without a comparison baseline.
- The system does not substitute for final engineering review.
Next case
04 / Applied ML · evaluation + rolloutASR evaluation → product