Risk-management layer with six patterns, four-level escalation, governance-adjustable thresholds.
Deployed; stress-tested; governance changing thresholds in production.
Before Sentinel, Proof had zero risk-management infrastructure. No velocity limits, no concentration caps, no correlation monitoring, no emergency pause.
Origin
Capital protocols accumulate risk silently until they don't. Velocity, concentration, correlation, and migration shocks are the four families of failure that have ended more on-chain instruments than every smart-contract bug combined. Proof had none of these protections wired up. Sentinel is the layer that turned every implicit assumption into a named, governance-adjustable threshold and a four-level escalation path the system actually walks under stress.
Problem
Risk management as an afterthought is risk management that doesn't run. The thresholds have to live in the same substrate the protocol's other state lives in, queryable by every primitive that touches a position, and adjustable through governance without redeploying the protocol. Anything else is theatre.
Approach
Six explicit risk patterns, each with a parameter set and an action: a velocity limiter on repricings and predictions, a concentration cap at the participant and instrument level, a correlation monitor that catches simultaneous downgrades, a pause and kill switch with multisig and timelock, a migration throttle on redemption pressure, and a multi-frame deviation monitor that watches the rolling mean across multiple windows. Every pattern has a name, a documented threshold, and a concrete action. Nothing is implicit.
Methodology
Four-level escalation: log, alert with soft block, hard block with governance review, kill switch with clawback to the insurance buffer. All thresholds are governance-adjustable through the protocol's own voting mechanism. A single master middleware sits in front of every protocol-level write call; nothing touches state without passing through it.
Selected milestones
Deployed end-to-end with full stress-test coverage
Clawback chain verified under live degradation conditions
Governance proposal → vote → execution changed thresholds in production
Open questions
How to handle correlated risk across structurally dissimilar instruments where the correlation is real but non-obvious
Whether the kill-switch timelock should adjust based on the pattern that triggered it
How threshold drift itself should be monitored — what's the meta-layer for the layer's own parameters
Ask me about
How governance changes a threshold without breaking the receipt chain
What the relationship is between this layer and the Operator-Tranche clawback
How a single master middleware integrates with every protocol write call
Why each pattern has a numeric threshold rather than a qualitative escalation rule