Know what your team is shipping with AI
Daily adoption metrics, sync health, and project-level breakdowns.
You bought 22 licenses. Are 22 developers using them?
Without measurement, you don't know. Half could be power users; half could have never opened the tool. You discover this at renewal — months too late.
In our own 29-seat rollout, 7 developers never ran a single session — 24% ghost rate. Read how we found them and recovered $1,400/month →
One glance shows you everything
Real-time per-developer activity, broken-setup detection, daily standup metrics — all without changing your team's workflow.
Your best prompts are stuck on one laptop
When we audited our own team's sessions, we found 14 different prompts doing the same job. The best produced 3× better output than the worst. No one knew a better version existed.
A shared, version-controlled Skills Library surfaces these patterns automatically — and syncs approved skills to every machine within 3 minutes. Read the prompt standardization data post →
Tracking GitHub Copilot seat utilisation across your team requires pulling per-seat activity data from the GitHub REST API — the native dashboard only shows 28-day active user counts and misses developers who go dark after week two. See our step-by-step guide to tracking GitHub Copilot usage across your engineering team →
Rolling out Claude Code to your engineering team follows a four-week structure: pilot with 3–5 volunteers in week one, expand and fix broken setups in week two, detect ghost seats in week three, and lock in habits before novelty fades in week four. Teams that follow this structure reach 75%+ weekly active developer rates at day 30; teams that provision everyone on day one average 45–55%. Read the 30-day Claude Code rollout playbook for engineering managers →