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MEASUREMENT BLUEPRINT · REVIEWED 4 SEPTEMBER 2026

Issue description to reviewed code change

Does an AI coding stack improve delivery without increasing escaped defects, security findings or review burden?

BEFORE THE PILOT

Record a credible baseline.

  1. 01Cycle time for comparable issues
  2. 02Reviewer minutes per accepted change
  3. 03Defects or security findings after merge
CONTROLLED WORKFLOW

Four accountable stages.

01

Select ten representative tasks with acceptance tests.

02

Apply repository, secret and dependency boundaries.

03

Require tests, explanation and a reviewable diff.

04

Compare accepted completion rate against the existing workflow.

STARTING SHORTLIST

Test the role, not the logo.

Product access and pricing change. Read the dated review, confirm supplier terms and run each tool against the same acceptance rules.

CU
Code AI

Cursor

AI-assisted software development inside an editor

9.1/10
GH
Code AI

GitHub Copilot

Mainstream coding assistance across IDEs and GitHub

8.9/10
n8
Automation AI

n8n

Technical teams building controllable AI and app workflows

9/10
MEASURE

Decision metrics

  • Accepted completion rate
  • Reviewer minutes
  • Test pass rate
  • Escaped defect rate
STOP / GO CONTROLS

Non-negotiable gates

  • Secrets and production data stay outside prompts.
  • Human review remains mandatory.
  • Generated dependencies receive the normal security checks.
AFTER THE TEST

Report the failures as carefully as the gains.

State the sample, dates, people, tool plans, accepted-output definition and correction effort. A useful result can be reproduced; a marketing claim cannot.

Read HubAI methodology