Agent Versioning & Change Management
Integrated change management system for enterprise agent prompts, models, deployment strategies, and governance
Integrated change management system for enterprise agent prompts, models, deployment strategies, and governance
AIDLC integration guide for 4 frameworks: EU AI Act, NIST AI RMF, ISO/IEC 42001, and Korea AI Basic Act
AIDLC Enterprise Adoption — Organizational transformation, cost estimation, governance, and case studies
Progressive model replacement strategies and Feature Flag-based prompt rollout approaches
EU AI Act risk classification, High-risk AI obligations, GPAI provider duties, and AIDLC integration guide
AWS Labs AIDLC Extension System — integrate organization-specific security, compliance, and domain rules into AIDLC workflows via opt-in mechanism
Regression detection, automatic rollback, approval workflows, audit trails, and AIDLC stage-specific application approaches
Required harnesses and implementation guide by MSA pattern
ISO/IEC 42001:2023 AI Management System PDCA structure, Annex A Controls, certification process, and AIDLC integration guide
Korea AI Basic Act's high-impact AI impact assessment, generative AI labeling obligations, PIPA/ISMS-P cross-compliance, and AIDLC integration guide
Application guide for Level 1 simple CRUD services and Level 2 synchronous MSA orchestration patterns
Application guide for Level 3 async event-driven MSA and Level 4 Saga + compensating transaction patterns
Application guide for Level 5 distributed transactions + CQRS + Event Sourcing patterns
Diagnose MSA difficulty as Level 1-5 in enterprise environments and provide integrated pattern-specific guides, harnesses, and verification
NIST AI Risk Management Framework 1.1's 4 Functions (GOVERN/MAP/MEASURE/MANAGE) and AIDLC integration guide
Ontology depth and writing guidelines by MSA complexity level
Comparison and implementation guide for Langfuse, PromptLayer, Braintrust, AWS Bedrock Prompt Management
Practical implementation guide and phased adoption roadmap for integrating regulatory requirements into AIDLC process
Verification methods to ensure quality when applying AIDLC in complex MSA