mission-control/documents/ai-adoption-meta-learning-loops-plan.md

Implementation Plan: Nine Meta-Learning Loops Integration

Overview

Integrate Vox's 9 meta-learning loops framework into Mission Control's autonomous agent system to enable closed-loop operations and progression toward full agent autonomy.

Current State Analysis

Strengths:

• Alice/Bob/Charlie workflow established
• API-centric CLI pattern prevents duplication
• Gantt Board provides task orchestration
• Research → Document → Task pipeline works

Gaps:

• No cap gates for agent overreach prevention
• No reaction matrix for standardized responses
• No proposal service for agent coordination
• No self-healing/stale task detection
• Missing autonomy progression tracking

Proposed Implementation

Phase 1: Safety Mechanisms (Week 1-2)

1.1 Cap Gates System

Location: /lib/agents/cap-gates.ts
- Max review cycles: 3 before human escalation
- Max token spend per task: 100k tokens
- Max execution time: 2 hours per agent session
- Forbidden operations: Require explicit approval

1.2 Reaction Matrix

Location: /lib/agents/reaction-matrix.ts
Standardized responses for:
- API failures → Retry with backoff
- Syntax errors → Check SKILL.md first
- Test failures → Run debug skill
- Research complete → Handoff to Bob
- Implementation stuck → Escalate to human

Phase 2: Coordination Layer (Week 3-4)

2.1 Proposal Service

Location: /lib/agents/proposals/
- Agent submits proposal: "I want to do X"
- Check against cap gates
- Validation against current sprint
- Auto-approve if within bounds
- Human approval if exceeds limits

2.2 Proposal Protocol

{
  "proposalId": "uuid",
  "agentId": "alice-researcher",
  "type": "research|implement|test",
  "estimatedCost": "tokens",
  "estimatedTime": "minutes",
  "requiresApproval": true|false,
  "rationale": "string",
  "expectedOutput": "string"
}

Phase 3: Self-Healing (Week 5-6)

3.1 Stale Task Detection

Location: /lib/agents/health-check.ts
- Cron every 30 minutes
- Check tasks with status "in-progress" > 30 min
- Query agent status via sessions_list
- If agent stalled: Respawn or escalate
- Update task with diagnostic comment

3.2 Recovery Actions

- Agent crashed → Respawn with context
- Agent stuck → Spawn debugger agent
- Task unclear → Add clarification request
- Resource exhausted → Queue for off-peak

Phase 4: Observability (Week 7-8)

4.1 Agent Dashboard (Mission Control Phase 8)

• Real-time agent status
• Token usage per agent
• Success/failure rates
• Time-to-completion metrics
• Autonomy level progression

4.2 Learning Metrics

• Which patterns succeed most
• Common failure modes
• Optimal task sizes
• Best agent combinations

Integration Points

With Existing Systems

System	Integration Point	Change Required
Gantt Board	Task status API	Add stale detection trigger
Mission Control	Documents API	Link research → plans
Agent Workflow	Spawn protocol	Add cap gate checks
Session Logs	Query API	Health check queries

File Changes

NEW: /lib/agents/cap-gates.ts
NEW: /lib/agents/reaction-matrix.ts
NEW: /lib/agents/proposal-service.ts
NEW: /lib/agents/health-check.ts
NEW: /lib/agents/dashboard.ts
MODIFY: /agents/TEAM-REGISTRY.md
MODIFY: Skill files for Alice/Bob/Charlie (add cap checks)

Risks and Mitigation

Risk	Impact	Mitigation
Cap gates too restrictive	Agents can't work	Start permissive, tighten based on data
Proposal overhead	Slower execution	Auto-approve 90% of cases
False stale detection	Interrupted work	Require 3 checks before action
Dashboard complexity	Delayed Phase 8	Build incrementally

Success Criteria

• Zero runaway agent incidents
• 95% auto-approval rate for proposals
• <5 min stale detection latency
• 50% reduction in human intervention needs
• Complete audit trail of agent decisions

Timeline

• Week 1-2: Cap gates + reactions
• Week 3-4: Proposal service
• Week 5-6: Self-healing
• Week 7-8: Dashboard

Dependencies

• Requires current agent workflow to be stable
• Gantt Board API token access
• Session log query capability
• Session list/monitoring tools

Rollout Strategy

1. Deploy cap gates (observation mode)
2. Enable reaction matrix
3. Launch proposal service (with manual approval)
4. Enable auto-approval after 1 week
5. Add stale detection
6. Build dashboard incrementally

Verdict: ADOPT

This plan directly addresses Mission Control's Phase 6-9 roadmap using a proven pattern from Vox. Start with Phase 1 safety mechanisms before enabling more autonomy.