DAO-Constrained Allocation
DAOs define hard limits on AI behavior through on-chain policies. Recommendations that satisfy all constraints can auto-execute; others require governance approval.
The Governance Challenge
DAOs face a dilemma when delegating capital management to AI:
Too Much Trust
Giving AI full autonomy means the DAO loses control. A rogue or manipulated AI could drain the treasury into a single high-risk protocol.
Too Little Trust
Requiring governance votes for every rebalance is slow and expensive. Markets move faster than DAOs can vote.
Obsqra.fi solves this with constraint-based autonomy: the DAO defines the boundaries, and the AI operates freely within them.
How Constraints Work
Set policy parameters
Generate allocation
On-chain validation
If all constraints pass
Set policy parameters
Generate allocation
On-chain validation
If all constraints pass
Constraint Types
Prevents concentration risk by limiting how much can go to any single protocol.
Requires allocation across multiple protocols to reduce single-point-of-failure risk.
Sets a ceiling on the average risk score across the portfolio.
Limits how much the allocation can shift in a single rebalance, preventing sudden large movements.
Auto-Approval Flow
When the AI generates a recommendation, the contract checks each constraint.
| Scenario | Auto-Execute? | Reason |
|---|---|---|
| 40/35/25 split, risk score 45 | Yes | All constraints satisfied |
| 60/25/15 split, risk score 45 | No | Exceeds max single protocol (60% > 50%) |
| 50/50/0 split, risk score 45 | No | Only 2 protocols (< 3 minimum) |
| 40/35/25 split, risk score 80 | No | Volatility too high (80 > 75) |
| Manual approval enabled | No | DAO requires vote for all changes |
Governance Override
When auto-execution is blocked, the recommendation enters a governance queue.
Auto-execute blocked
Enters governance
Token holders decide
If approved
Auto-execute blocked
Enters governance
Token holders decide
If approved
requiresManualApproval = true during market stress to pause all auto-execution. This is a safety mechanism that does not require changing individual constraint values.Best Practices
Do
- +Start with conservative limits
- +Gradually relax as trust builds
- +Monitor constraint violations
- +Have emergency pause capability
- +Review policies quarterly
Don't
- -Set limits too loose initially
- -Ignore constraint violations
- -Remove all constraints
- -Use single-sig for governance
- -Forget to test edge cases