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Get Started: LinearB Trial Setup Guide
LinearB Trial Setup. This document will walk you through the process of getting your LinearB trial started.
Learn how LinearB maps your code → review → release pipeline and connects DORA metrics, AI insights, and automation to help your team continuously improve delivery.
What is LinearB?
LinearB is an engineering delivery optimization platform that connects your Git provider, project management tool, and (optionally) 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, LinearB focuses on improvement. It identifies bottlenecks, highlights root causes, and provides actionable guidance and automation to help teams ship faster with higher quality and better predictability.
What LinearB helps you do
- Accelerate delivery by reducing long PR review time, 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 visibility into cycle time, throughput, and investment across teams.
- Adopt AI responsibly by detecting AI tools and measuring their impact on delivery and quality.
- Automate developer workflows with gitStream, reducing repetitive manual steps in the PR process.
In short: LinearB helps teams improve how they build and deliver software—not just observe it.
From Insight to Action
Most tools surface metrics. LinearB connects those metrics to actions that improve them.
The platform connects metrics directly to levers teams can act on, including:
- AI-powered code review to reduce manual review effort and identify risk earlier.
- Pull request automations (via gitStream) that standardize workflows and remove manual steps.
- Team Goals that translate performance signals into trackable improvement targets.
- Bottleneck detection that identifies where work slows down and why.
- AI adoption tracking that links AI usage to delivery and quality outcomes.
This combination of measurement, action, and automation differentiates LinearB from traditional reporting tools.
The Delivery Pipeline Explained
LinearB visualizes the flow of work across three core stages:
- Open — Developers create branches and start committing code.
- Merge — A pull request enters the review and approval workflow.
- Release — Code merges into the main branch and moves through the release process to production.
These stages form the pull request funnel and help you understand:
- Where work slows down (review time, pickup time, PR size)
- How long each stage takes
- How AI-assisted work compares to non-AI work
By connecting this flow to metrics such as cycle time, throughput, and quality, LinearB provides a clear view of how work moves from code to production.
DORA Metrics Overview
LinearB automatically calculates and visualizes your DORA metrics using Git, deployment, and optional incident data:
- Deployment Frequency — How often code is deployed to production.
- Lead Time for Changes — Time from first commit to production.
- Change Failure Rate (CFR) — Percentage of deployments that result in incidents.
- Mean Time to Recovery (MTTR) — Time required to restore service after an incident.
LinearB uses first-party Git and deployment data to keep these metrics accurate and consistent without manual tagging or spreadsheets.
DORA provides a benchmarkable view of engineering performance. LinearB connects each metric to the underlying behaviors that influence it, enabling teams to improve how they work—not just track results.
To explore definitions, calculations, and usage, see the Metrics Glossary .
You’re now ready to explore how LinearB helps your teams improve delivery and operate more efficiently.
How did we do?
LinearB: Core Concepts
