Ten minutes · ten areas

How ready is your codebase for AI-native delivery?

Ten areas, scored 0 to 3. The same ten our readiness assessment measures, scored by you instead of by us. You get a score and the three areas to fix first, on this page.

0 = not in place · 1 = partly, informally · 2 = in place, not enforced · 3 = in place and enforced by tooling

1. Coding standards: written down, and checked by the build rather than by reviewers

0 1 2 3

2. Automated tests: enough that a change can be trusted without a manual pass

0 1 2 3

3. Modular boundaries: a change in one area does not require understanding the whole system

0 1 2 3

4. Machine-readable documentation: what the product does is written where a tool can read it, and it is current

0 1 2 3

5. Decision records: why things are the way they are is recorded, not remembered

0 1 2 3

6. Pipeline: a change goes from commit to a reviewable, tested build without manual steps

0 1 2 3

7. Branch protection and review: nothing reaches the main branch without a person approving it

0 1 2 3

8. Traceability: any change can be traced to the requirement it came from and the release it went out in

0 1 2 3

9. AI governance: accounts are the organisation's, attributable to a person, with rules on what tools may read and write

0 1 2 3

10. Measurement: you can say, per team and per quarter, how fast you deliver and how much goes wrong

0 1 2 3

Organisation *

Engineers

Work email *

Your name and role

Why these ten

AI tools amplify whatever process they land in

Give an AI a codebase with enforced standards, real tests and current documentation, and it delivers safely at speed. Give it the opposite and it produces plausible changes faster than anyone can check them. The ten areas are the difference, and the first four are where most organisations score lowest.

Read on

Readiness assessment

Two weeks, fixed price, the same ten areas measured rather than estimated.

AI-native engineering

What the framework looks like once the gaps are closed.

Case study: AI-native engineering

A software organisation's before and after.