Role-Based Navigation Guide

Every role has a different relationship with AI-assisted engineering. With 92% of US developers now using AI tools daily and AI co-authored code showing 1.7x more issues and a 2.74x higher vulnerability rate, the stakes for getting adoption right are enormous -- but the approach varies dramatically depending on your seat at the table. This section provides curated reading paths so that each role can quickly find the standards, practices, and recommendations most relevant to their responsibilities.

How to Use This Section

The AEEF Standards framework is organized around five pillars that apply universally. However, how you engage with those pillars depends on your role. A developer needs hands-on prompt engineering techniques; a CTO needs architecture governance patterns; an executive needs board-ready metrics. This section translates the universal framework into role-specific guidance.

Step 1: Identify your primary role from the table below. Step 2: Follow the link to your role's overview page. Step 3: Work through the sub-pages in order -- they are sequenced from foundational to advanced. Step 4: Use the cross-references to dive deeper into specific standards or pillars when you need more detail.

tip

Many professionals wear multiple hats. If you are a tech lead who also manages people, read both the Developer Guide and the Development Manager Guide. If you are a CTO at a startup who also writes code, add the Developer Guide to your reading list.

Role-to-Guide Mapping

Role	Guide	Primary Focus	Key Standards	Key Pillars
Software Developer / Engineer	Developer Guide	Daily workflows, prompt engineering, code review, security	PRD-STD-002, PRD-STD-003, PRD-STD-005	Pillar 1: Engineering Discipline, Pillar 2: Quality Assurance
Development Manager / Engineering Manager	Development Manager Guide	Team enablement, quality oversight, metrics, performance	PRD-STD-001, PRD-STD-006	Pillar 3: Governance & Oversight, Pillar 5: Organizational Alignment
Scrum Master / Agile Coach	Scrum Master Guide	Sprint adaptation, estimation, ceremonies, team health	PRD-STD-004, PRD-STD-006	Pillar 4: Continuous Improvement, Pillar 5: Organizational Alignment
Product Manager / Product Owner	Product Manager Guide	Roadmap planning, stakeholder expectations, velocity trade-offs	PRD-STD-004, PRD-STD-001	Pillar 4: Continuous Improvement, Pillar 3: Governance & Oversight
CEO / Executive	Executive Guide	Strategy, risk governance, ROI, competitive positioning	PRD-STD-006, PRD-STD-007	Pillar 3: Governance & Oversight, Pillar 5: Organizational Alignment
CTO / VP Engineering	CTO Guide	Technology strategy, architecture, build vs. buy, org design	PRD-STD-001, PRD-STD-005, PRD-STD-007	Pillar 1: Engineering Discipline, Pillar 3: Governance & Oversight
QA Lead / Test Lead	QA Lead Guide	Testing strategy, AI-generated tests, defect analysis, automation	PRD-STD-003, PRD-STD-002	Pillar 2: Quality Assurance, Pillar 1: Engineering Discipline

Cross-Role Dependencies

Effective AI-assisted engineering requires collaboration across roles. The following matrix shows where guides intersect and where cross-role conversations are most critical.

Topic	Roles Involved	Why It Matters
Quality gates for AI code	Developer, QA Lead, Dev Manager	Everyone must agree on what "good enough" means for AI-generated code
Sprint velocity recalibration	Scrum Master, Product Manager, Developer	AI changes delivery speed unevenly; all parties need shared expectations
Tool selection and provisioning	CTO, Dev Manager, Developer	Tool choices cascade through the entire engineering organization
Risk governance	Executive, CTO, Dev Manager	Board-level risk reporting depends on ground-level risk identification
Investment justification	Executive, CTO, Product Manager	ROI models require input from both technical and product perspectives
Security posture	Developer, QA Lead, CTO	The 2.74x vulnerability rate in AI code requires vigilance at every level

Reading Paths by Maturity Level

If your organization is just beginning its AI-assisted engineering journey, the reading order matters. Use the Maturity Model to assess your current level, then follow the appropriate path.

Level 1 -- Exploring (Weeks 1-4)

1. Start with the Executive Guide: Strategic Imperative for organizational context
2. Read the Developer Guide: Daily Workflows for hands-on orientation
3. Review the CTO Guide: Technology Strategy for tool selection
4. Consult the QA Lead Guide: Testing Strategy for quality baselines

Level 2 -- Adopting (Months 2-3)

1. Work through the full Developer Guide end-to-end
2. Implement the Scrum Master Guide: Sprint Adaptation processes
3. Establish the Development Manager Guide: Metrics That Matter dashboards
4. Begin Product Manager Guide: Roadmap Planning adjustments

Level 3 -- Scaling (Months 4-6)

1. Deploy the full Development Manager Guide framework
2. Calibrate using Scrum Master Guide: Estimation in an AI World
3. Optimize with CTO Guide: Architecture Considerations
4. Report progress using Executive Guide: Board-Ready Metrics

Level 4-5 -- Optimizing and Leading

1. All role guides should be fully implemented
2. Focus shifts to continuous improvement and industry leadership
3. Use the Maturity Model for ongoing self-assessment

Keeping Current

The AI-assisted engineering landscape evolves rapidly. Each role guide includes a "What to Watch" section highlighting emerging trends. We recommend:

• Monthly: Review your role guide for updated practices
• Quarterly: Re-assess your maturity level using the Maturity Model
• Annually: Conduct a full cross-role alignment review using the dependency matrix above

info

These role guides are designed to complement, not replace, the core AEEF Standards and Five Pillars. Always refer to the authoritative standards documents when establishing formal policies or governance structures.