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Agentic AI Atlas · self-optimization
lib-skill:shared--self-optimizationa5c.ai
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self-optimization overview

SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.

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displayName
self-optimization
description
SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.
libraryPath
library/methodologies/ruflo/skills/self-optimization/SKILL.md
contentSummary
- Improving routing and agent selection over time - Adapting to new project patterns without forgetting old ones - Building cross-session intelligence ## SONA Cycle 1. **Extract Patterns** - Mine execution data for recurring patterns 2. **RETRIEVE** - Search ReasoningBank for matching traje

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lib_applies_to_domain1
  • domain:software-engineering·DomainSoftware Engineering
lib_covers_topic1
  • topic:developer-experience·TopicDeveloper Experience (DX)
lib_implements_workflow1
  • workflow:feature-development·Workflow
lib_involves_role2
  • role:tech-lead·RoleTech Lead
  • role:backend-engineer·RoleBackend Engineer
lib_requires_skill_area2
  • skill-area:agentic-loops·SkillAreaAgentic Loops
  • skill-area:orchestration-loop·SkillAreaOrchestration Loop Engineering

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