Implement intelligent agent learning from Knowledge Graph execution history with per-task-type expertise tracking, recency bias, and learning curves. ## Phase 5.3 Implementation ### Learning Infrastructure (✅ Complete) - LearningProfileService with per-task-type expertise metrics - TaskTypeExpertise model tracking success_rate, confidence, learning curves - Recency bias weighting: recent 7 days weighted 3x higher (exponential decay) - Confidence scoring prevents overfitting: min(1.0, executions / 20) - Learning curves computed from daily execution windows ### Agent Scoring Service (✅ Complete) - Unified AgentScore combining SwarmCoordinator + learning profiles - Scoring formula: 0.3*base + 0.5*expertise + 0.2*confidence - Rank agents by combined score for intelligent assignment - Support for recency-biased scoring (recent_success_rate) - Methods: rank_agents, select_best, rank_agents_with_recency ### KG Integration (✅ Complete) - KGPersistence::get_executions_for_task_type() - query by agent + task type - KGPersistence::get_agent_executions() - all executions for agent - Coordinator::load_learning_profile_from_kg() - core KG→Learning integration - Coordinator::load_all_learning_profiles() - batch load for multiple agents - Convert PersistedExecution → ExecutionData for learning calculations ### Agent Assignment Integration (✅ Complete) - AgentCoordinator uses learning profiles for task assignment - extract_task_type() infers task type from title/description - assign_task() scores candidates using AgentScoringService - Fallback to load-based selection if no learning data available - Learning profiles stored in coordinator.learning_profiles RwLock ### Profile Adapter Enhancements (✅ Complete) - create_learning_profile() - initialize empty profiles - add_task_type_expertise() - set task-type expertise - update_profile_with_learning() - update swarm profiles from learning ## Files Modified ### vapora-knowledge-graph/src/persistence.rs (+30 lines) - get_executions_for_task_type(agent_id, task_type, limit) - get_agent_executions(agent_id, limit) ### vapora-agents/src/coordinator.rs (+100 lines) - load_learning_profile_from_kg() - core KG integration method - load_all_learning_profiles() - batch loading for agents - assign_task() already uses learning-based scoring via AgentScoringService ### Existing Complete Implementation - vapora-knowledge-graph/src/learning.rs - calculation functions - vapora-agents/src/learning_profile.rs - data structures and expertise - vapora-agents/src/scoring.rs - unified scoring service - vapora-agents/src/profile_adapter.rs - adapter methods ## Tests Passing - learning_profile: 7 tests ✅ - scoring: 5 tests ✅ - profile_adapter: 6 tests ✅ - coordinator: learning-specific tests ✅ ## Data Flow 1. Task arrives → AgentCoordinator::assign_task() 2. Extract task_type from description 3. Query KG for task-type executions (load_learning_profile_from_kg) 4. Calculate expertise with recency bias 5. Score candidates (SwarmCoordinator + learning) 6. Assign to top-scored agent 7. Execution result → KG → Update learning profiles ## Key Design Decisions ✅ Recency bias: 7-day half-life with 3x weight for recent performance ✅ Confidence scoring: min(1.0, total_executions / 20) prevents overfitting ✅ Hierarchical scoring: 30% base load, 50% expertise, 20% confidence ✅ KG query limit: 100 recent executions per task-type for performance ✅ Async loading: load_learning_profile_from_kg supports concurrent loads ## Next: Phase 5.4 - Cost Optimization Ready to implement budget enforcement and cost-aware provider selection.
570 lines
14 KiB
Markdown
570 lines
14 KiB
Markdown
# 🔄 Multi-Agent Workflows
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## End-to-End Parallel Task Orchestration
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**Version**: 0.1.0
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**Status**: Specification (VAPORA v1.0 - Workflows)
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**Purpose**: Workflows where 10+ agents work in parallel, coordinated automatically
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---
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## 🎯 Objetivo
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Orquestar workflows donde múltiples agentes trabajan **en paralelo** en diferentes aspectos de una tarea, sin intervención manual:
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```
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Feature Request
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↓
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ProjectManager crea task
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↓ (paralelo)
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Architect diseña ────────┐
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Developer implementa ────├─→ Reviewer revisa ──┐
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Tester escribe tests ────┤ ├─→ DecisionMaker aprueba
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Documenter prepara docs ─┤ ├─→ DevOps deploya
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Security audita ────────┘ │
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↓
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Marketer promociona
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```
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---
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## 📋 Workflow: Feature Compleja End-to-End
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### Fase 1: Planificación (Serial - Requiere aprobación)
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**Agentes**: Architect, ProjectManager, DecisionMaker
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**Timeline**: 1-2 horas
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```yaml
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Workflow: feature-auth-mfa
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Status: planning
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Created: 2025-11-09T10:00:00Z
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Steps:
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1_architect_designs:
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agent: architect
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input: feature_request, project_context
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task_type: ArchitectureDesign
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quality: Critical
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estimated_duration: 45min
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output:
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- design_doc.md
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- adr-001-mfa-strategy.md
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- architecture_diagram.svg
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2_pm_validates:
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dependencies: [1_architect_designs]
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agent: project-manager
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task_type: GeneralQuery
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input: design_doc, project_timeline
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action: validate_feasibility
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3_decision_maker_approves:
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dependencies: [2_pm_validates]
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agent: decision-maker
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task_type: GeneralQuery
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input: design, feasibility_report
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approval_required: true
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escalation_if: ["too risky", "breaks roadmap"]
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```
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**Output**: ADR aprobado, design doc, go/no-go decision
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---
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### Fase 2: Implementación (Paralelo - Máxima concurrencia)
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**Agentes**: Developer (×3), Tester, Security, Documenter (async)
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**Timeline**: 3-5 días
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```yaml
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4_frontend_dev:
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dependencies: [3_decision_maker_approves]
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agent: developer-frontend
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skill_match: frontend
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input: design_doc, api_spec
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tasks:
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- implement_mfa_ui
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- add_totp_input
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- add_webauthn_button
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parallel_with: [4_backend_dev, 5_security_setup, 6_docs_start]
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max_duration: 4days
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4_backend_dev:
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dependencies: [3_decision_maker_approves]
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agent: developer-backend
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skill_match: backend, security
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input: design_doc, database_schema
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tasks:
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- implement_mfa_service
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- add_totp_verification
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- add_webauthn_endpoint
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parallel_with: [4_frontend_dev, 5_security_setup, 6_docs_start]
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max_duration: 4days
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5_security_audit:
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dependencies: [3_decision_maker_approves]
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agent: security
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input: design_doc, threat_model
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tasks:
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- threat_modeling
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- security_review
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- vulnerability_scan_plan
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parallel_with: [4_frontend_dev, 4_backend_dev, 6_docs_start]
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can_block_deployment: true
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6_docs_start:
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dependencies: [3_decision_maker_approves]
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agent: documenter
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input: design_doc
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tasks:
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- create_adr_doc
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- start_implementation_guide
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parallel_with: [4_frontend_dev, 4_backend_dev, 5_security_audit]
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low_priority: true
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Status: in_progress
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Parallel_agents: 5
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Progress: 60%
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Blockers: none
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```
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**Output**:
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- Frontend implementation + PRs
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- Backend implementation + PRs
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- Security audit report
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- Initial documentation
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---
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### Fase 3: Código Review (Paralelo pero gated)
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**Agentes**: CodeReviewer (×2), Security, Tester
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**Timeline**: 1-2 días
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```yaml
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7a_frontend_review:
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dependencies: [4_frontend_dev]
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agent: code-reviewer-frontend
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input: frontend_pr
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actions: [comment, request_changes, approve]
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must_pass: 1 # At least 1 reviewer
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can_block_merge: true
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7b_backend_review:
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dependencies: [4_backend_dev]
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agent: code-reviewer-backend
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input: backend_pr
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actions: [comment, request_changes, approve]
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must_pass: 1
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security_required: true # Security must also approve
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7c_security_review:
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dependencies: [4_backend_dev, 5_security_audit]
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agent: security
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input: backend_pr, security_audit
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actions: [scan, approve_or_block]
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critical_vulns_block_merge: true
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high_vulns_require_mitigation: true
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7d_test_coverage:
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dependencies: [4_frontend_dev, 4_backend_dev]
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agent: tester
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input: frontend_pr, backend_pr
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actions: [run_tests, check_coverage, benchmark]
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must_pass: tests_passing && coverage > 85%
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Status: in_progress
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Parallel_reviewers: 4
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Approved: frontend_review
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Pending: backend_review (awaiting security_review)
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Blockers: security_review
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```
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**Output**:
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- Approved PRs (if all pass)
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- Comments & requested changes
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- Test coverage report
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- Security clearance
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---
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### Fase 4: Merge & Deploy (Serial - Ordered)
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**Agentes**: CodeReviewer, DevOps, Monitor
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**Timeline**: 1-2 horas
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```yaml
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8_merge_to_dev:
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dependencies: [7a_frontend_review, 7b_backend_review, 7c_security_review, 7d_test_coverage]
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agent: code-reviewer
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action: merge_to_dev
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requires: all_approved
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9_deploy_staging:
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dependencies: [8_merge_to_dev]
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agent: devops
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environment: staging
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actions: [trigger_ci, deploy_manifests, smoke_test]
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automatic_after_merge: true
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timeout: 30min
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10_smoke_test:
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dependencies: [9_deploy_staging]
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agent: tester
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test_type: smoke
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environments: [staging]
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must_pass: all
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11_monitor_staging:
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dependencies: [9_deploy_staging]
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agent: monitor
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duration: 1hour
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metrics: [error_rate, latency, cpu, memory]
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alert_if: error_rate > 1% or p99_latency > 500ms
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Status: in_progress
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Completed: 8_merge_to_dev
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In_progress: 9_deploy_staging (20min elapsed)
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Pending: 10_smoke_test, 11_monitor_staging
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```
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**Output**:
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- Code merged to dev
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- Deployed to staging
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- Smoke tests pass
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- Monitoring active
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---
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### Fase 5: Final Validation & Release
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**Agentes**: DecisionMaker, DevOps, Marketer, Monitor
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**Timeline**: 1-3 horas
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```yaml
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12_final_approval:
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dependencies: [10_smoke_test, 11_monitor_staging]
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agent: decision-maker
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input: test_results, monitoring_report, security_clearance
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action: approve_for_production
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if_blocked: defer_to_next_week
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13_deploy_production:
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dependencies: [12_final_approval]
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agent: devops
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environment: production
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deployment_strategy: blue_green # 0 downtime
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actions: [deploy, health_check, traffic_switch]
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rollback_on: any_error
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14_monitor_production:
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dependencies: [13_deploy_production]
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agent: monitor
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duration: 24hours
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alert_thresholds: [error_rate > 0.5%, p99 > 300ms, cpu > 80%]
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auto_rollback_if: critical_error
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15_announce_release:
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dependencies: [13_deploy_production] # Can start once deployed
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agent: marketer
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async: true
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actions: [draft_blog_post, announce_on_twitter, create_demo_video]
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16_update_docs:
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dependencies: [13_deploy_production]
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agent: documenter
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async: true
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actions: [update_changelog, publish_guide, update_roadmap]
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Status: completed
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Deployed: 2025-11-10T14:00:00Z
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Monitoring: Active
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Release_notes: docs/releases/v1.2.0.md
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```
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**Output**:
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- Deployed to production
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- 24h monitoring active
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- Blog post + social media
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- Docs updated
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- Release notes published
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---
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## 🔄 Workflow State Machine
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```
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Created
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↓
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Planning (serial, approval-gated)
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├─ Architect designs
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├─ PM validates
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└─ DecisionMaker approves → GO / NO-GO
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↓
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Implementation (parallel)
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├─ Frontend dev
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├─ Backend dev
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├─ Security audit
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├─ Tester setup
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└─ Documenter start
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↓
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Review (parallel but gated)
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├─ Code review
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├─ Security review
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├─ Test execution
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└─ Coverage check
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↓
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Merge & Deploy (serial, ordered)
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├─ Merge to dev
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├─ Deploy staging
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├─ Smoke test
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└─ Monitor staging
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↓
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Release (parallel async)
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├─ Final approval
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├─ Deploy production
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├─ Monitor 24h
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├─ Marketing announce
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└─ Docs update
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↓
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Completed / Rolled back
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Transitions:
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- Blocked → can escalate to DecisionMaker
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- Failed → auto-rollback if production
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- Waiting → timeout after N hours
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```
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---
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## 🎯 Workflow DSL (YAML/TOML)
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### Minimal Example
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```yaml
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workflow:
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id: feature-auth
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title: Implement MFA
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agents:
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architect:
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role: Architect
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parallel_with: [pm]
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pm:
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role: ProjectManager
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depends_on: [architect]
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developer:
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role: Developer
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depends_on: [pm]
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parallelizable: true
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approval_required_at: [architecture, deploy_production]
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allow_concurrent_agents: 10
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timeline_hours: 48
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```
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### Complex Example (Feature-complete)
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```yaml
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workflow:
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id: feature-user-preferences
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title: User Preferences System
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created_at: 2025-11-09T10:00:00Z
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phases:
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phase_1_design:
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duration_hours: 2
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serial: true
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steps:
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- name: architect_designs
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agent: architect
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input: feature_spec
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output: design_doc
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- name: architect_creates_adr
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agent: architect
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depends_on: architect_designs
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output: adr-017.md
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- name: pm_reviews
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agent: project-manager
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depends_on: architect_creates_adr
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approval_required: true
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phase_2_implementation:
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duration_hours: 48
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parallel: true
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max_concurrent_agents: 6
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steps:
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- name: frontend_dev
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agent: developer
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skill_match: frontend
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depends_on: [architect_designs]
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- name: backend_dev
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agent: developer
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skill_match: backend
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depends_on: [architect_designs]
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- name: db_migration
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agent: devops
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depends_on: [architect_designs]
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- name: security_review
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agent: security
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depends_on: [architect_designs]
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- name: docs_start
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agent: documenter
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depends_on: [architect_creates_adr]
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priority: low
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phase_3_review:
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duration_hours: 16
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gate: all_tests_pass && all_reviews_approved
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steps:
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- name: frontend_review
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agent: code-reviewer
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depends_on: frontend_dev
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- name: backend_review
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agent: code-reviewer
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depends_on: backend_dev
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- name: tests
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agent: tester
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depends_on: [frontend_dev, backend_dev]
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- name: deploy_staging
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agent: devops
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depends_on: [frontend_review, backend_review, tests]
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phase_4_release:
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duration_hours: 4
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steps:
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- name: final_approval
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agent: decision-maker
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depends_on: phase_3_review
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- name: deploy_production
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agent: devops
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depends_on: final_approval
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strategy: blue_green
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- name: announce
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agent: marketer
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depends_on: deploy_production
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async: true
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```
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---
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## 🔧 Runtime: Monitoring & Adjustment
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### Dashboard (Real-Time)
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```
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Workflow: feature-auth-mfa
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Status: in_progress (Phase 2/5)
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Progress: 45%
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Timeline: 2/4 days remaining
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Active Agents (5/12):
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├─ architect-001 🟢 Designing (80% done)
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├─ developer-frontend-001 🟢 Implementing (60% done)
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├─ developer-backend-001 🟢 Implementing (50% done)
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├─ security-001 🟢 Auditing (70% done)
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└─ documenter-001 🟡 Waiting for PR links
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Pending Agents (4):
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├─ code-reviewer-001 ⏳ Waiting for frontend_dev
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├─ code-reviewer-002 ⏳ Waiting for backend_dev
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├─ tester-001 ⏳ Waiting for dev completion
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└─ devops-001 ⏳ Waiting for reviews
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Blockers: none
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Issues: none
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Risks: none
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Timeline Projection:
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- Design: ✅ 2h (completed)
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- Implementation: 3d (50% done, on track)
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- Review: 1d (scheduled)
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- Deploy: 4h (scheduled)
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Total ETA: 4d (vs 5d planned, 1d early!)
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```
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|
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### Workflow Adjustments
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|
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```rust
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pub enum WorkflowAdjustment {
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// Add more agents if progress slow
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AddAgent { agent_role: AgentRole, count: u32 },
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// Parallelize steps that were serial
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Parallelize { step_ids: Vec<String> },
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// Skip optional steps to save time
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SkipOptionalSteps { step_ids: Vec<String> },
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// Escalate blocker to DecisionMaker
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EscalateBlocker { step_id: String },
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// Pause workflow for manual review
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Pause { reason: String },
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// Cancel workflow if infeasible
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Cancel { reason: String },
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}
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|
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// Example: If timeline too tight, add agents
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if projected_timeline > planned_timeline {
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workflow.adjust(WorkflowAdjustment::AddAgent {
|
||
agent_role: AgentRole::Developer,
|
||
count: 2,
|
||
}).await?;
|
||
}
|
||
```
|
||
|
||
---
|
||
|
||
## 🎯 Implementation Checklist
|
||
|
||
- [ ] Workflow YAML/TOML parser
|
||
- [ ] State machine executor (Created→Completed)
|
||
- [ ] Parallel task scheduler
|
||
- [ ] Dependency resolution (topological sort)
|
||
- [ ] Gate evaluation (all_passed, any_approved, etc.)
|
||
- [ ] Blocking & escalation logic
|
||
- [ ] Rollback on failure
|
||
- [ ] Real-time dashboard
|
||
- [ ] Audit trail (who did what, when, why)
|
||
- [ ] CLI: `vapora workflow run feature-auth.yaml`
|
||
- [ ] CLI: `vapora workflow status --id feature-auth`
|
||
- [ ] Monitoring & alerting
|
||
|
||
---
|
||
|
||
## 📊 Success Metrics
|
||
|
||
✅ 10+ agents coordinated without errors
|
||
✅ Parallel execution actual (not serial)
|
||
✅ Dependencies respected
|
||
✅ Approval gates enforce correctly
|
||
✅ Rollback works on failure
|
||
✅ Dashboard updates real-time
|
||
✅ Workflow completes in <5% over estimated time
|
||
|
||
---
|
||
|
||
**Version**: 0.1.0
|
||
**Status**: ✅ Specification Complete (VAPORA v1.0)
|
||
**Purpose**: Multi-agent parallel workflow orchestration
|