Tempered AI Assessment

intermediate 2 hours Assessment

Measure, benchmark, and improve your AI-assisted development

Evaluate your team's AI-assisted development maturity across 12 research-backed dimensions. Get personalized recommendations based on your current practices and industry benchmarks.

For: Developers , Team Leads , Executives

Start Assessment Answer questions across 12 dimensions to get personalized recommendations

What You’ll Learn

• Understand your team's current AI maturity level
• Identify gaps compared to industry benchmarks
• Get actionable recommendations for improvement
• Create a prioritized roadmap for AI adoption

Dimensions

1

Foundational Adoption

Assess basic activation and consistent usage of Copilot tools across interfaces. With 90% industry adoption in 2025, this is table stakes — but agentic interfaces now matter more.

10 min

2

Context Curation

Assess how effectively your team provides relevant context to AI tools through project rules, documentation, and data injection.

10 min

3

Model Routing

Assess your practices for choosing the right AI model for different tasks based on cost, latency, and capability requirements.

10 min

4

Agentic Supervision

Assess your practices for supervising autonomous AI agents. As AI gains more autonomy, supervision and guardrails become critical.

15 min

5

Trust Calibration

Assess whether your team's trust in AI outputs matches actual AI capabilities. Over-trust leads to bugs; under-trust leads to missed value.

15 min

6

Appropriate Non-Use

Assess your team's judgment about when NOT to use AI — recognizing scenarios where AI adds risk, cost, or complexity without benefit.

12 min

7

Organizational Integration

Assess how AI tools are integrated into team workflows, training, and organizational processes.

10 min

8

Legal & Compliance

Assess compliance with IP, privacy, security, and regulatory requirements when using AI coding tools.

12 min

9

Team Composition

Assess how AI is changing team roles, skill requirements, and hiring practices.

8 min

10

Legacy Modernization

Assess how effectively AI tools are used for understanding, documenting, and modernizing legacy codebases.

8 min

11

Advanced Workflows

Assess adoption of advanced AI workflows: spec-driven development, graphs, multi-step orchestration.

10 min

12

Business Outcomes

Assess measurable business outcomes: productivity, quality, developer satisfaction, and ROI from AI adoption.

10 min