The AI-Enabled SDLC Delivery Model
A comprehensive, five-pillar framework for systematically embedding AI across your entire software delivery lifecycle. Designed for enterprise adoption — structured, measurable, and proven.
01. AI Development Workflow
Redesign how code is written, reviewed, and shipped by embedding AI into daily development workflows. Move beyond individual productivity tools to systematic workflow transformation.
Key Activities
- AI-assisted code generation workflow design
- Intelligent code review and pair programming models
- Prompt engineering standards and best practices
- Developer experience optimization with AI tooling
- Metrics: cycle time, throughput, developer satisfaction
02. AI-Driven Testing & QA
Transform quality assurance from manual bottleneck to AI-accelerated competitive advantage. Intelligent test generation, automated regression analysis, and predictive defect detection.
Key Activities
- AI-powered test case generation and maintenance
- Visual regression testing with AI comparison
- Predictive defect analysis and risk-based testing
- Test coverage optimization through AI analysis
- Metrics: defect escape rate, test coverage, QA cycle time
03. Architecture & Design Evolution
Evolve your technical architecture to support AI-native development patterns. From AI-assisted design decisions to architecture documentation that stays current through AI analysis.
Key Activities
- AI-assisted architectural decision records (ADRs)
- Automated architecture documentation and visualization
- Technical debt identification and prioritization via AI
- Design pattern recommendations based on codebase analysis
- Metrics: architecture fitness functions, tech debt ratio
04. AI Governance & Risk
Establish governance structures that enable responsible AI adoption without bureaucratic drag. Risk frameworks, compliance controls, and acceptable use policies designed for engineering teams.
Key Activities
- AI acceptable use policy development
- Risk assessment framework for AI-generated code
- Compliance mapping and audit trail design
- IP and licensing governance for AI tools
- Metrics: compliance score, policy adherence, risk incidents
05. Team & Operating Model Transformation
Redesign team structures, roles, and operating models for the AI-augmented era. New skills, new roles, and new ways of working that unlock the full potential of AI-enabled delivery.
Key Activities
- Role evolution mapping (from current to AI-augmented)
- Skills assessment and training program design
- Team topology redesign for AI-native workflows
- Change management and cultural transformation
- Metrics: adoption rate, team velocity, retention
Assess Your AISDM Readiness
Start with a structured assessment to understand where you stand across all five pillars.