TempoA clearer way to reason about engineering systems.
Practical guides to engineering metrics, AI coding analytics, measurement methodology, and the data behind Tempo integrations.
Engineering intelligence
Understand delivery flow and connect AI adoption to outcomes without turning activity into individual performance scores.
Engineering metrics for software teams
Track PR flow, deployments, work health, collaboration, and AI adoption from GitHub, Jira, and Linear.
Read the guide →Developer productivity metrics that support better decisions
Choose developer productivity metrics across delivery flow, developer experience, quality, and outcomes without ranking people by activity.
Read the guide →PR cycle time: definition and calculation
PR cycle time measures elapsed time from pull-request creation to merge or closure. See p50, p90, pickup time, and review time.
Read the guide →AI coding & impact
Measure adoption from evidence, connect it to delivery outcomes, and understand the limits of attribution.
AI coding analytics for engineering teams
Measure AI coding adoption and compare its impact on PR cycle time, review load, PR size, and delivery flow.
Read the guide →How to measure the impact of AI coding tools
Measure AI coding adoption, delivery flow, review load, quality constraints, and cost without confusing correlation with productivity.
Read the guide →AI coding detection methodology
Learn how Tempo detects AI-assisted commits using local session evidence, git metadata, confidence levels, and privacy-preserving attribution.
Read the guide →AI commit rate: definition and calculation
AI commit rate is the share of non-merge commits with detected AI assistance. Learn how Tempo calculates and interprets it.
Read the guide →Tool selection
Choose engineering measurement tools from the data, operating model, and decisions your team actually needs.
Integrations
Learn what Tempo syncs from your engineering tools and how those sources combine into a system-level view.
GitHub engineering metrics integration
Connect GitHub to Tempo for PR flow, reviews, commits, deployments, repository analytics, and AI coding attribution.
Read the guide →Jira engineering metrics integration
Connect Jira Cloud to Tempo for issue cycle time, throughput, WIP, stale work, epic progress, and links to pull requests.
Read the guide →Linear engineering metrics integration
Connect Linear to Tempo for issue cycle time, throughput, WIP, stale work, project progress, and delivery context.
Read the guide →Put the ideas into practice.
Connect your engineering tools and explore Tempo with your own delivery data.
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