Build blueprint
Semantic Feature-Flag Allocator
A policy layer selecting safe UI variants based on session intent, friction, and risk.
- Problem
- Feature flags target static cohorts but cannot react intelligently to the current session.
- Why Jev
- Allocation needs a typed variant choice at request time with uncertainty-aware fallback.
- Architecture
- Approved session features → Jev variant Choice → deterministic eligibility checks → flag result.
- Current alternative
- Rule trees and broad A/B cohorts.
- Jev advantage
- Enables per-event adaptation while code retains the final eligibility boundary.
- Unknowns
- Fairness, explainability, and feedback loops from adaptive assignment.
Why this confidence: Architecture is novel but carries experimentation and fairness risks.
This is an authored hypothesis derived from the research corpus. Nothing here demonstrates product demand, or that Jev performs well on this particular workload. Run the validation experiment before building past the MVP.
Sources
Limitations
- Fairness, explainability, and feedback loops from adaptive assignment.
- This is a research hypothesis, not evidence of product demand or Jev performance in this workflow.
Supporting research
- Probabilistic predicate + deterministic action PlausibleJev supplies fuzzy predicates while TypeScript, policies, and workflows execute constrained actions.
- HA-Jev ObservedA Home Assistant custom integration exposing Jev evaluations as sensors and automation actions.
- Cheap decision calls could make tens or hundreds of semantic judgments per event economical. SpeculativeThe product design follows from published pricing and parallel question primitives, not independent production evidence.
- Decision sidecar PlausibleA typed judgment service sits beside ordinary code; code owns effects and safety boundaries.