Guides · Practical teaching

Better questions.
Clearer decisions.

Field guides for engineering leaders measuring whether AI coding seats produce a return. Independent research, clearly labeled vendor telemetry, and decisions you can act on.
Take the 60-second self-check

Written by Alex Tong, previously at Amazon and The New York Times. Start with the tool you use, or the renewal decision in front of you. Alex also runs live workshops for engineering teams.

  1. Claude Code

    How to Measure Claude Code ROI (When You Can't Tell If the Spend Is Working)

    Measure Claude Code ROI using idle seats, delivery throughput, and review time. A practical guide to comparing actual outcomes with your pre-AI baseline.

    Read the guide
  2. Cursor

    How to Measure Cursor ROI: A Metrics Method for Engineering Leaders

    Measure Cursor ROI before renewal using idle seats, pull-request throughput, review time, and your pre-AI baseline. Grounded in independent research.

    Read the guide
  3. GitHub Copilot

    How to Measure GitHub Copilot ROI (Without Trusting Acceptance Rate)

    Measure GitHub Copilot ROI with idle seats, pull-request throughput, review time, and a pre-AI baseline. Compare license spend with actual delivery outcomes.

    Read the guide
  4. The renewal decision

    Should You Renew Your AI Coding Seats? A Decision Guide

    Use idle-seat, throughput, and review-time data to decide whether to keep, renegotiate, fix, or cut AI coding seats. A guide for engineering leaders.

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Put it into practice

Check what you can measure.

Five questions about adoption, delivery, and review. Use the answers to choose the next metric to collect. No signup required.

Take the 60-second self-check