About the Assessment

The Tempered AI Assessment evaluates your organization’s effectiveness with AI-assisted development across 12 research-backed dimensions. Unlike simple adoption metrics, this assessment measures the skills that actually predict success in the AI-assisted development era.

2025 Paradigm Shift

The industry has moved from Chat/Autocomplete to the Agentic/Supervisor paradigm. Models like Claude Opus 4.5 (80.9% SWE-bench) perform chain-of-thought automatically—the bottleneck has shifted from prompting to context curation and agent supervision.

Why This Assessment Exists

The research is clear: AI adoption without skill development creates problems.

89%

of organizations are prioritizing AI integration Source: DORA 2025

45%

of AI-generated code introduces security vulnerabilities Source: Veracode 2025

39%

of developers trust AI output only “a little” or “not at all” Source: DORA 2025

451%

increase in AI adoption when organizations have clear policies Source: DORA 2025

The core insight: AI amplifies existing organizational strengths and weaknesses. Mature AI usage isn’t about maximizing adoption—it’s about developing the skills to use AI appropriately, safely, and effectively.

The 12 Dimensions

Each dimension is weighted based on research showing its impact on developer productivity, code quality, and organizational outcomes.

Core Skills (65% of total weight)

Context Curation & Specification 18%

The #1 skill gap. Providing the right files, docs, and project context to AI tools.

Trust Calibration & Verification 17%

Knowing when to trust vs. verify. Neither blind acceptance nor paranoid rejection.

Agentic Workflow Supervision 15%

Managing autonomous AI workflows that edit multiple files without constant intervention.

Appropriate Non-Use & Managed Use 15%

Knowing when NOT to use AI. Security-critical code, novel algorithms, audit requirements.

Strategic Capabilities (35% of total weight)

Foundational Adoption 10%

Basic activation and consistent daily usage patterns.

Model Selection & Routing 10%

Matching tasks to appropriate models (cost, capability, latency tradeoffs).

Organizational Integration 10%

Enterprise policies, governance structures, and team-wide standards.

Legal & IP Compliance 5%

Regulatory requirements (HIPAA, SOC2), IP considerations, licensing.

Supplemental Dimensions (not scored)

These dimensions are collected for insights but excluded from the maturity score. They either measure subjective perception, apply only to specific roles, or represent frontier capabilities not yet widely adopted.

Advanced Multi-Session Workflows excluded

Multi-model orchestration, custom MCP servers, agentic pipelines.

Legacy System & Specialized Use Cases excluded

Using AI for legacy codebase documentation, refactoring, and migration.

Perceived Outcomes & Satisfaction excluded

Measuring actual results: velocity, quality, developer satisfaction.

Team Composition & Talent Development excluded

Balancing experience levels. Junior developers need different AI support than seniors.

Assessment Philosophy

Maturity ≠ Maximum Usage

High AI usage without skill development leads to technical debt, security vulnerabilities, and false confidence. Mature organizations use AI appropriately—sometimes that means not using it at all.

This assessment is designed around three principles:

1. Research-backed — Every question cites peer-reviewed research or industry data from DORA, Veracode, GitHub/Accenture, and METR.

2. Actionable — Results include specific recommendations for individuals and teams, not just a score.

3. Self-demonstrating — This platform practices what it preaches. Every claim is source-backed. The architecture demonstrates the structured outputs, type safety, and configuration-driven patterns we recommend.

What You’ll Get

After completing the assessment, you’ll receive:

• Overall maturity score with industry benchmarking
• Dimension-by-dimension breakdown showing strengths and gaps
• Personalized recommendations prioritized by impact (critical → low)
• Progression guidance with specific next steps to reach the next maturity level
• Exportable results (JSON) for team discussions and tracking progress over time

Research Sources

This assessment draws from:

Source	Type	Key Contribution
DORA State of AI-Assisted Development 2025	Research Report	Adoption rates, trust calibration, organizational factors
Veracode GenAI Code Security Report 2025	Security Research	AI code vulnerability rates, security patterns
METR Developer Productivity Study 2025	Academic Research	Experienced developer performance with AI
Qodo State of AI Code Quality 2025	Industry Survey	Error rates, review patterns
GitHub/Accenture Enterprise Research	Industry Report	Acceptance rates, code retention

Ready to Begin?

The assessment takes 15-20 minutes and can be completed in multiple sessions (progress is saved locally).

Start Assessment Evaluate your team's AI-assisted development maturity across 12 dimensions