AI engineering metrics
Codiedev Reports answers engineering leaders' questions from their Codiedev reporting, right in the conversation. Ask how engineering is doing this month, whether AI-assisted pull requests actually merge faster, which repositories drive AI spend, how adoption is going on a team, or which models people use and how reliable they are.
Who it's for: company admins, CTOs and team managers whose company uses Codiedev to capture AI coding sessions and pull requests. Admins see the whole company and can narrow to any team. Team managers see only their own team and never see spend. Engineers can't connect.
What it can do: read delivery and cycle-time stages, the AI-vs-no-AI comparison with its classification coverage, velocity and the throughput forecast, daily activity and rate-limit pressure, adoption and skill reuse, model usage and reliability, capture coverage, and (admins only) spend versus the prior period, ROI, cost per merge, seats and the spend forecast.
Limitations: it is read-only and can't change anything in Codiedev. It reports team and company aggregates, not individual session transcripts. Numbers come from stored rollups refreshed about hourly, over 30, 60 or 90-day windows, and only cover sessions Codiedev captured; every answer can quote capture coverage so you know how complete it is. A Codiedev account with the Admin or Team manager role is required.
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