Is your engineering team actually AI-native, or just using AI tools?

Most engineering leaders think their teams are AI-enabled. They're not — they're using AI tools the same way they used to use Stack Overflow: individually, inconsistently, with no shared standard and no way to measure the result. This assessment shows you exactly where the gaps are, and what to fix first.

15 questions
5 minutes
Instant results
No login

The difference between AI-assisted and AI-native

Not AI-native
  • AI struggles to understand your codebase
  • Engineers afraid to refactor
  • Estimates are wild guesses
  • Tests written after bugs are found
  • PRs take days to review
  • Tech debt growing quarter over quarter
AI-native
  • AI generates correct code on the first try
  • Refactoring is safe, fast, and common
  • Estimates track within 20% of actual
  • Tests written before or alongside code
  • PRs reviewed same day, small and clear
  • Tech debt reducing every quarter
The 4 maturity levels
L1
Ad-hoc AI Use
You're experimenting
  • ›Context lives in engineers' heads
  • ›AI tools used individually
  • ›No way to measure impact
L2
Assisted Development
You've got adoption
  • ›Most engineers use AI tools
  • ›Practices vary by engineer
  • ›Some coverage, inconsistent
L3Target
AI-Native
The target for most teams
  • ›80%+ PRs involve AI
  • ›Tests alongside every change
  • ›Cycle time under 5 days
L4
Advanced / Agentic
You're at the frontier
  • ›Agentic workflows running autonomously
  • ›Context is infrastructure
  • ›Small teams, 2× output

What you'll get

01
Your maturity level
L1 to L4: where your team sits on the path to AI-native engineering.
02
Where AI is slowing you down
Five dimensions that separate teams who ship faster with AI from those who've just added a new tab to their browser.
03
Your 3 next actions
Specific, prioritised steps to reach the next level. Not generic advice.
15 questions
5 minutes
Instant results
No login
5 dimensions assessed
Context Infrastructure
AI Adoption Rate
Testing & Verification
Delivery Patterns
Measurement & Visibility
Irfan Suleman
Technology & Engineering Leader · Fractional CTO

20+ years building digital platforms that scale. I've led 50-person engineering organisations, scaled digital revenue to $100M, shipped Apple-featured products at Mindvalley, and deployed platforms across 31 global markets at Standard Chartered.

If you're here from the AI Maturity Assessment: this call is to walk through your results and talk about what the path to L3 looks like for your specific team. No pitch. 30 minutes.