Six connected stages. One continuous approach to quality.
From understanding where you are today to scaling what works, each stage answers a question every engineering leader faces. Start where it matters most to you.
AI-enabled and agentic systems raise new questions about behaviour, evidence, context, autonomy, controls and continuous evaluation. The methodology handles them as one connected approach rather than separate initiatives.
Iterative, not linear: evidence and change can trigger reassessment at any stage.
Pick the statement that sounds most like your team.
Where does our Quality Engineering stand today?
The IQE Maturity Model assesses Quality Engineering capability across nine dimensions. Rather than relying only on a single maturity score, it creates a capability profile that helps identify strengths, gaps and priorities.
The objective is not necessarily to reach the highest level in every dimension. Appropriate maturity depends on organizational context, risk and business need.
- Strategy & Leadership
- People & Skills
- Process & Ways of Working
- Automation & Engineering
- Architecture & Testability
- Data & Test Environments
- DevOps & Continuous Quality
- Metrics & Business Outcomes
- AI & Agentic QE
A current-state maturity profile, priority gaps and a 30/60/90-day roadmap.
- 01 · ReactiveQuality is verified late, largely through manual effort, in response to problems rather than by design.
- 02 · AutomatedAutomation accelerates verification, but is still primarily focused on repeating existing tests faster.
- 03 · IntelligentEvidence, telemetry and continuous learning begin to inform engineering and quality decisions.
- 04 · AgenticQuality Engineering incorporates governed agentic capabilities with defined boundaries, evidence and human oversight.
- 05 · AdaptiveQuality Engineering continuously evolves using evidence, operational signals and changing system behavior.
How do we move from here to our target state?
Move from current state toward a target operating model through a structured, staged transformation path.
The IQE Maturity Model is used during Discover, and measurement continues throughout the transformation.
A target operating approach and a prioritized transformation path.
- DiscoverUnderstand current state, priorities, constraints and evidence.
- DesignDefine the target operating approach and transformation priorities.
- PilotTest selected changes in a controlled environment.
- IndustrializeIntegrate proven practices into engineering and delivery.
- ScaleExpand adoption while maintaining governance, evidence and learning.
How do we make quality continuous, not a phase?
The IQE Loop represents the continuous operating rhythm of Intelligent Quality Engineering. Signals are observed, context is modeled, quality is engineered, outcomes are evaluated, controls are applied and learning feeds the next cycle.
A repeatable rhythm that keeps quality improving between releases.
- SenseSignals are observed.
- ModelContext is modeled.
- EngineerQuality is engineered.
- EvaluateOutcomes are evaluated.
- GovernControls are applied.
- LearnLearning feeds the next cycle.
How do we oversee systems that reason, plan and act?
When systems can reason, plan, use tools and take actions, Quality Engineering must examine more than whether the final answer appears correct. The Agentic QE Control Plane provides a structured view of the controls and evidence needed around agent behavior.
A control framework around agent behaviour, from intent to traceability.
Agent Behavior → Controls → Quality Evidence
Control Plane Elements- IntentIs the agent pursuing the right goal?
- PlanningIs its plan sound and within scope?
- EvidenceAre its reasoning and results supported by evidence?
- Tool UseAre tools used correctly and only as permitted?
- Action SafetyAre actions within safe, approved boundaries?
- RecoveryCan failures be detected and recovered?
- OutcomeIs the final result correct and useful?
- TraceabilityCan every decision and action be traced?
Can we prove our quality claims?
Quality decisions become more defensible when claims about system quality can be traced to relevant evidence. Quality Evidence Architecture connects engineering activity, evaluation results, controls and operational signals to the decisions they support.
Traceable evidence behind every quality and release decision.
- Engineering Activity
- Quality Evidence
- Quality / Risk Decision
How do we prove value before scaling?
The 30/60/90 Adoption Path is an implementation playbook nested within the Pilot stage of the Transformation Lifecycle.
The 30/60/90 path is intended for focused adoption and validation, not as a promise that enterprise transformation can be completed within 90 days.
A focused, evidence-based pilot and a clear decision on what to scale.
- 30 DaysBaseline, select the use case and define evidence.
- 60 DaysPilot the approach, evaluate outcomes and refine controls.
- 90 DaysDemonstrate value, document learning and decide what should scale.
Not sure where to begin? Start with the assessment.
The Intelligent QE Maturity Assessment maps your current capability and gives you a prioritized 30/60/90-day roadmap.
A proposed practical model informed by Quality Engineering practice, emerging AI assurance approaches, engineering experimentation and practitioner perspectives. It will evolve as evidence grows. See our research →