Governance Workflows

Status: MVP for ADAPTIVE-WP-0008.

Purpose

This milestone turns pricing outputs into governed workflows instead of standalone metrics.

The repository now exposes:

a governance policy model
governed seller recommendations
a customer-facing safe-tuning contract surface
pricing health checks
provider-publication audit and revision surfaces

Core And Adapter Layers

Generic core:

adaptive_pricing_core/governance.py

Coulomb adapter:

projects/coulomb-pricing/observatory/governance.py
projects/coulomb-pricing/data/governance_policy.json

Governance Policy

The policy model covers:

approval thresholds
customer-visible price-change rules
experiment capacity
candidate rollout limits
provider execution limits
customer communication ownership
grandfathering and notice expectations
customer-visible tuning enablement

For Coulomb, the current policy keeps customer-visible tuning disabled and requires approval for candidate rollouts and approximate Stripe mappings.

Recommendation Workflow

Recommendations now include:

recommendation type: research, simulation, model change, or execution
rationale
confidence
risks
supporting observations
governance decision
approval requirements

This satisfies the PRD requirement that recommendations be explainable and distinguish between evidence gathering, simulation, model design, and execution.

Safe-Tuning Contract

The governance surface exposes a structured contract for customer-tunable pricing:

allowed tunable parameters
a trade-off lexicon
pilot examples
whether a model is customer-visible or still pilot-only

For the current Coulomb MVP, the contract exists only as a pilot surface for membership-plus-overage; accepted examples are still seller-assisted rather than self-serve.

Health And Audit

The dashboard payload now includes:

pricing health checks
provider execution readiness checks
tuning pilot health
experiment capacity checks
provider revision history and active revision metadata

These surfaces are intended to help both humans and agents decide whether the next safe step is research, simulation, approval, execution, or rollback.

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