Quick Assessment

Quick AI Maturity Check

10 questions · 2 minutes · Shareable results

Move each slider to reflect your current practices. Results update in real-time.

Answer all 10 questions to see results 0/10

1. How often do you use AI coding tools?

Consider GitHub Copilot, Cursor, Claude, ChatGPT, etc.

Never Multiple times daily

2. How skilled are you at providing effective context to AI tools?

Including @file references, rules files, and structured prompts.

Just ask questions Expert context curation

3. How deliberately do you choose AI models for different tasks?

Fast models for simple tasks, powerful models for complex ones.

Use one model for everything Strategic model selection

4. How well do you supervise AI agents working autonomously?

Reviewing diffs, using checkpoints, catching scope creep.

Let it run freely Systematic oversight

5. How appropriately skeptical are you of AI-generated code?

In controlled testing, 45% of unreviewed AI code had security flaws (varies by language).

Accept most suggestions Verify systematically

6. How good are you at knowing when NOT to use AI?

Security-critical code, skill maintenance, compliance boundaries.

Use AI for everything Strategic non-use decisions

7. How well is AI integrated into your team's practices?

Shared guidelines, standard workflows, training programs.

Individual use only Team-wide standards

8. How aware are you of AI code licensing and IP concerns?

License compliance, attribution requirements, legal risks.

Not aware Compliance processes in place

9. How effective is AI at helping you work with legacy code?

Understanding old codebases, migrations, documentation.

Not applicable / No help Essential for legacy work

10. How advanced are your AI development workflows?

Spec-driven development, multi-agent orchestration, persistent sessions.

Basic chat only Advanced orchestration

Tempered AI — Forged Through Practice, Not Hype

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