LinearB: Core Concepts

LinearB is an engineering delivery optimization platform that connects your Git provider, project management tool, and (optional) incident system to create a unified view of how work moves from code → review → release → production, while linking that activity back to the issues, epics, and services your teams are responsible for.

Unlike traditional reporting tools that simply measure activity, LinearB focuses on improvement. It identifies bottlenecks, highlights the underlying causes, and provides actionable guidance and automations to help teams ship faster, with higher quality and better predictability.

• Accelerate delivery by reducing long PR review times, large PR size, and slow pickup time.
• Improve code quality with AI-assisted review and risk signals tied to your code and incidents.
• Increase predictability with clear visibility into cycle time, throughput, and investment across teams.
• Adopt AI responsibly by detecting 50+ AI tools and measuring their downstream impact on delivery and quality.
• Automate developer workflows with gitStream, reducing repetitive manual steps in the PR process.

In short: LinearB helps teams continuously improve the way they build and deliver software, not just observe it.

LinearB visualizes the flow of work across four core stages of the engineering lifecycle:

1. Open — Developers create branches and start committing code.
2. Merge — A pull request is opened and enters the review and approval workflow.
3. Release — Code merges into your main branch and moves through your release process.
4. No Rollback — Code successfully reaches production without rollback.

These stages represent the pull request funnel and allow you to understand:

• Where work gets stuck (long reviews, waiting for pickup, large PRs)
• How long each stage takes and how it contributes to overall cycle time
• How AI-assisted work behaves compared to non-AI work

By tying this flow to metrics like cycle time, throughput, and quality, LinearB gives you a realistic view of how work actually moves from code to production.

LinearB automatically calculates and visualizes your DORA metrics using Git, deployment, and (optionally) incident data:

• Deployment Frequency — How often your team deploys code to production.
• Lead Time for Changes (Cycle Time) — How long it takes a code change to go from first commit to production.
• Change Failure Rate (CFR) — The share of deployments that lead to incidents or require remediation.
• Mean Time to Recovery (MTTR) — How long it takes to restore service after an incident.

LinearB uses first-party Git and deployment metadata to keep these metrics accurate and consistent—no manual tagging or spreadsheets required.

DORA gives you a benchmarkable view of engineering performance. With LinearB, each metric is connected to the underlying behaviors that influence it, so teams can improve how they work, not just watch a number.

To dive deeper into how each metric is defined, calculated, and interpreted, see the full Metrics Glossary.

Most tools show you charts. LinearB helps you change the chart.

The platform is built around the idea that insight is only valuable if it leads to action. LinearB connects metrics directly to levers teams can pull, including:

• AI-powered code review to offload repetitive review work and highlight risky changes faster.
• Pull request automations (via gitStream) that standardize workflows and remove manual steps from the PR process.
• Team Goals that turn DORA and performance signals into specific, trackable improvement targets.
• Bottleneck detection that pinpoints where work slows down and why (for example, long review time vs. waiting for pickup).
• AI adoption and impact tracking across 50+ AI tools, linking AI usage to delivery and quality outcomes.

This combination of measurement + action + automation is what sets LinearB apart from traditional reporting tools.

• Get Started with the Enterprise (plan) Setup Guide
• Get Started with the Essentials (plan) Setup Guide