Processes
Explore lifecycle processes, operational workflows, and governance reviews that guide how teams build and operate across the AI Blueprint.
Lifecycle processes (xDLCs)
Agent Development Life Cycle (ADLC)
End-to-end lifecycle for building and deploying AI agents.
Lifecycle Agentic Core
Traditional
Ideate (APO)
Design (AIA)
Develop (AE)
Evaluate (AE)
Deploy (AE)
Run (ARE)
AI-Native
Specifies agent intent
Planning Agent
Eval Agents
Coding Agents
Eval Agents
Review & Deploy Agents
Refactoring Agents
Software Development Life Cycle (SDLC)
Standard software development lifecycle.
Lifecycle Software Core
Traditional
Plan (PO)
Design (SA)
Build (SWE)
Test (SWE)
Release (SWE)
Operate (SRE)
AI-Native
Specifies feature intent
Planning Agent
Test Agents
Coding Agents
Test Agents
Review & Release Agents
Refactoring Agents
Data Development Life Cycle (DDLC)
Lifecycle for data products and pipelines.
Lifecycle Data Core
Traditional
Discover (DPO)
Model (DA)
Build (DE)
Validate (DE)
Publish (DS)
Use (DRE)
AI-Native
DPO describes data need
Discovery Agents
Pipeline Agents
Quality Agents
Publish Agents
Monitor Agents
Foundation Development Life Cycle (FDLC)
Lifecycle for infrastructure and platform services.
Lifecycle Foundations
Traditional
Design (CPA)
Provision (PE)
Configure (PE)
Harden (CSE)
Operate (ISRE)
AI-Native
Architect describes infra need
IaC Agents
Security Agents
Deploy Agents
Monitor Agents
Cost Agents
Operational processes
Agent Incident Response
Process for responding to agent-related incidents.
Operational
Traditional
Detect (ARE)
Triage (ARE)
Investigate (ARE)
Remediate (AE)
Review (ARE)
AI-Native
Agent anomaly detected
Agent Anomaly Detection
Triage Agent
Agent RCA Agent
Agent Remediation
Postmortem Agent
Incident Response
Standard incident response for applications.
Operational
Traditional
Detect (SRE)
Triage (SRE)
Mitigate (SRE)
Resolve (SWE)
Review (SRE)
AI-Native
Alert fires or user reports issue
Anomaly Detection Agent
Triage Agent
RCA Agent
Remediation Agent
Postmortem Agent
Governance processes
Security Review
Security review for new deployments or changes.
Governance
Traditional
Request (SWE)
Assess (SEC)
Review (SEC)
Remediate (SWE)
Approve (SEC)
AI-Native
Change submitted for review
Classification Agent
Policy Evaluation Agent
Security Scanning Agent
Review Orchestration Agent
Monitoring Agent
AI Safety Review
Safety and ethics review for AI agent deployments.
Governance
Traditional
Submit (AE)
Assess (AEP)
Test (AEP)
Approve (AEP)
AI-Native
Agent submitted for safety review
Classification Agent
Safety Evaluation Agent
Red Team Agent
Review Orchestration Agent
Safety Monitoring Agent
Agent Development Life Cycle (ADLC)
End-to-end lifecycle for building and deploying AI agents.
Lifecycle Agentic core
Traditional
1
2
Design
Design agent architecture and prompts
Responsible: AI/ML architect (AIA)
Architecture reviewed
Components:
3
4
Evaluate
Test and evaluate agent performance
Responsible: Agent engineer (AE)
Eval thresholds met
Components:
5
6
Run
Monitor and optimize agent in production
Responsible: Agent reliability engineer (ARE)
Components:
AI-Native
Spec & Planning Planning Agent
Human role: Specifies intent declaratively
Outputs:
Architecture decisionsComponent selectionAmbiguity flags
Eval Design (TDD) Eval Agents
Human role: Defines success criteria
Outputs:
Eval datasetsAccuracy benchmarksRegression tests
Components:
Coding Coding Agents
Human role: Reviews direction
Outputs:
Agent codePromptsMCP toolsGuardrails
Local Validation Eval Agents
Human role: Iteratively tests in workspace
Outputs:
Local eval runsPrompt tuningBehavior validation
Components:
Release Train Review & Deploy Agents
Human role: Monitors pipeline
Outputs:
Security checksCanary deployArchitectural validation
Maintain & Refactor Refactoring Agents
Human role: Reviews suggestions periodically
Outputs:
Tech debt cleanupPrompt optimizationDependency updates
Components: