Recursive Self-Improvement
Governed recursive cycles that continuously optimize workflow topology, agent placement, and role-bound specifications. Every iteration feeds evidence into the next — never uncontrolled.
Continuous Self-Improvement,
Governed by Design.
Five stages cycle endlessly: observe decision patterns, analyze value conflicts, rewrite workflow topology, validate through gates, deploy with audit trail. Every cycle feeds evidence into the next.
Every Decision Source, One Substrate.
Normalize approvals, meetings, chat, PR reviews, and execution logs into a single event substrate with immutable timeline reconstruction.
Approvals
Ringi & sign-offs
Meetings
Minutes & notes
PR Reviews
Code decisions
Chat Logs
Slack, Teams
Exec Logs
Execution traces
Unified
Event Substrate
Immutable timeline
Audit-grade retention
Replay capability
Branch Detection
Value Attribution
Conflict Analysis
Find the Hidden Judgment Points.
Analyze ringi approval logs to identify decision branch points where outcomes diverge. Heatmap intensity reveals value conflict at each junction — the meta values behind each branch are the real architecture of your organization.
From Approval Documents to Judgment Architecture.
Every branch point, meta value tag, and value context extracted from approval documents feeds directly into the recursive improvement loop. MARIA OS services are internally connected — each extraction cycle sharpens the next.
Connected Services
Decision Scanner
Approval documents parsed into structured branch topology
Value Scanner
Meta value tags extracted at every judgment point
Workflow Scanner
Branch patterns fed back to rewrite workflow DAGs
Recursive Loop
Improved workflows generate new decisions — cycle repeats
Minimal Gates, Maximum Control.
Three gates is enough. Too many gates suffocate. Too few invite chaos. Each gate narrows the decision funnel — only governed actions pass through.
Industry Safety Gate
Regulatory, compliance, legal constraints. Non-negotiable.
BLOCKED
Regulatory violations, safety hazards, legal exposure
PASSES
All compliant decisions, standard operations
Company Value Gate
MVV alignment check. Blocks decisions that contradict practiced values.
BLOCKED
Value contradictions, strategic drift, culture violations
PASSES
MVV-aligned decisions, value-consistent actions
Structural Change Gate
Workflow redesign, role changes, parameter shifts. Always requires human approval.
BLOCKED
Unauthorized scope changes, privilege escalation, design rewrites
PASSES
Approved structural changes only
GOVERNED EXECUTION
Audited, traceable, reversible
Before Recursion vs. After Recursion.
Each recursive cycle identifies bottlenecks, removes redundant nodes, and optimizes approval topology. Workflow rewrites are treated as structural-change proposals — always gate-approved.
Nodes Reduced
9 → 6
-33%
Bottlenecks
2 → 0
-100%
Avg. Lead Time
5.2d → 1.8d
-65%
Repeat Rejections
28% → 4%
-86%
Role-Bound Agents, Evolving Specs.
Agents are placed by dependency pressure, not static quotas. Authority scope, risk budget, and approval thresholds evolve as versioned specs — never autonomously.
Zone Topology
Power
Capital
Institution
Mass
Narrative
Chaos
Spec Evolution
Read-only analytics
+ Low-risk execution
+ Cross-zone coordination
+ Structural proposals
Invariant: No agent can autonomously expand its own spec version. All upgrades require human approval through the Structural Change Gate.
Measure Every Recursive Cycle.
84
72
91
88
66
77
Run a Recursive Cycle
Evolution Is Permitted. Value Self-Modification Is Not.
Research visualization: what recursive self-improvement can and cannot touch
Improvable
Recursive self-improvement CAN optimize
- Goal evaluation functions
- Execution strategies
- Gate accuracy & precision
- Workflow topology
- Agent placement & roles
Protected
CANNOT be self-modified by AI
- Mission values (Vₘ)
- Core ethical principles
- Responsibility assignments
- Value vector dimensions
- Human authority boundaries
Override Gate
Mission updated ONLY under special conditions
- Human approval required
- Cooling period elapsed (24h+)
- Impact simulation completed
- All goals re-projected
- Change log permanently stored
V_m(t+1) = normalize(V_m(t) + ΔV)
only if HumanApproval
∧ CoolingPeriod
∧ ImpactAnalysisThe alignment evaluation algorithm evolves. The value axis does not. This is the civilizational principle of MARIA OS.