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gitStream - Start Here

Use this hub to understand what gitStream does, how LinearB helps you measure AI-driven development, how we handle security and privacy, and where to start with installation and low-noise automations…

heather.hazell
Updated by heather.hazell

Use this hub to understand what gitStream does, how LinearB helps you measure AI-driven development, how we handle security and privacy, and where to start with installation and low-noise automations.


gitStream Enablement

What is gitStream?

gitStream is LinearB’s automation engine for pull requests. It runs in your Git provider and lets you:

  • Automate PR policies (size, ownership, risk, approvals).
  • Route reviews to the right people based on expertise, files, or teams.
  • Apply AI to descriptions and reviews to reduce manual toil.
  • Enforce consistency while keeping PR noise as low as possible.

Instead of every team reinventing PR rules in different repos, gitStream centralizes your policies as code and applies them consistently across your organization.


AI: What LinearB Helps You Measure

Understanding the business impact of AI-assisted development

AI adoption is accelerating—but most engineering leaders still struggle to measure its true impact. LinearB helps you quantify how AI changes your workflow, code quality, delivery speed, and downstream stability.

Key questions LinearB answers:

  • Delivery speed
    • Is AI helping my teams ship faster?
    • How much faster—and where?
    • If not faster, what’s blocking improvements?
  • Code volume & merge efficiency
    • How much AI-generated code is being created?
    • How much of it actually gets merged?
    • How does AI-assisted code behave compared to non-AI code?
  • Stability & incidents
    • Which AI-assisted PRs reach production?
    • Which of them introduce incidents or rollbacks?
    • What’s the downstream impact on MTTR and CFR?
  • Code quality & maintainability
    • Is AI introducing:
      • Bugs
      • Security vulnerabilities
      • Maintainability issues
      • Performance regressions
      • Readability or scope problems
    • Do AI-generated changes result in higher churn?
  • Team impact
    • Which teams leverage AI effectively?
    • Which teams see bottlenecks, slowdowns, or increased rework?
    • How does AI adoption affect reviewer workload?

How LinearB & gitStream enable this:

  • Tag PRs influenced by AI tools or AI-generated code.
  • Measure how AI-influenced PRs move through the funnel (Open → Merge → Release → No Rollback).
  • Track performance differences between AI and non-AI changes.
  • Identify which AI-assisted PRs contribute to production issues.

With LinearB, AI shifts from guesswork to accountability—giving you clear visibility into the value and risks introduced by AI-driven coding.


Security & Privacy

How gitStream handles your code & data

At a high level, gitStream is designed to respect the same security and privacy principles as the rest of LinearB:

  • Read-only access: gitStream and LinearB read repository metadata and code only as needed to evaluate rules and AI prompts. They do not modify your code.
  • Least privilege: Installation scopes are limited to what is required for PR automation (for example: reading PRs, comments, reviews, and status checks).
  • Config as code: Your policies live in configuration files (YAML) in your repos or central configuration, giving you full visibility and change control.
  • AI usage transparency: Where AI is used (descriptions, review suggestions, summaries), gitStream clearly identifies AI-assisted actions.

For formal details, please refer to your LinearB's security portal. For access, please contact support


Execution Modes and Plan Availability

gitStream supports two execution modes (availability depends on your LinearB plan):

  • Managed ModeAvailable on the Essentials plan only.
    Automations run on LinearB’s managed runner and are controlled via simple toggles under Company Settings → AI Tools.
    No YAML files are required.
  • Self-Managed ModeAvailable on all plans, including Enterprise.
    Full customization using YAML files stored in your repository’s .cm directory. Automations execute inside your Git provider environment (e.g., GitHub Actions, GitLab CI, Bitbucket Pipelines).

Tip: If you do not see Managed Mode in your workspace, your plan uses Self-Managed Mode exclusively.


Install Overview & Time Estimates

Use this table to understand roughly how long each installation path takes and who needs to be involved.

Git Provider High-Level Method Approx. Time Difficulty Who Performs This?
GitHub Cloud Install GitHub App 2–5 minutes ⭐ Easy GitHub Org Admin
GitHub Enterprise Server Custom GitHub App 5–10 minutes ⭐⭐ Medium GitHub Enterprise Admin
GitLab (SaaS / Self-Managed) Personal Access Token + Webhooks / CI 10–15 minutes ⭐⭐ Medium GitLab Maintainer / Owner
Bitbucket Cloud OAuth Consumer + Webhooks 10–15 minutes ⭐⭐ Medium Workspace Admin
Essentials (Managed Mode) Enable toggles under AI Tools 1–3 minutes ⭐ Very Easy LinearB Admin

Step 1 — Confirm Your Prerequisites

  • Your Git provider is already connected to LinearB (via Settings → Integrations → Git).
  • You know which provider you are using (GitHub, GitLab, Bitbucket).
  • You have (or can get) admin-level access for installing apps / tokens / webhooks.
  • You’ve decided whether you will use Managed Mode (Essentials only) or Self-Managed Mode.

Step 2 — Choose Your Installation Guide

Each section below gives a short “at a glance” summary plus a link to the full, provider-specific setup guide.

GitHub Cloud — Install GitHub App

Time: 2–5 minutes  |  Difficulty: ⭐ Easy

High-level flow:

  1. Go to LinearB → Automations → gitStream.
  2. Select GitHub Cloud and click Install App.
  3. Choose your GitHub organization.
  4. Install for all repositories (recommended) or a subset.
  5. Return to LinearB and confirm repositories appear under gitStream.

Verification: Open a test PR and confirm gitStream automations fire once YAML or Managed Mode rules are enabled.

Full guide: GitStream for GitHub Cloud — Installation Guide

GitHub Enterprise Server — Custom GitHub App

Time: 5–10 minutes  |  Difficulty: ⭐⭐ Medium

High-level flow:

  1. Create a Custom GitHub App in your Enterprise instance.
  2. Configure required permissions (PRs, comments, checks, labels).
  3. Set webhooks to the endpoint provided by LinearB.
  4. Generate a private key and copy the App ID / secrets into LinearB.
  5. Install the app on the target organization(s).

Full guide: GitStream for GitHub Enterprise Server — Installation Guide

GitLab (SaaS or Self-Managed)

Time: 10–15 minutes  |  Difficulty: ⭐⭐ Medium

High-level flow:

  1. Create a Personal Access Token with api scope.
  2. In LinearB, go to Automations → gitStream and select GitLab.
  3. Enter the token and GitLab URL (for self-managed).
  4. Select which projects/repositories gitStream should monitor.
  5. Configure webhooks / CI according to the detailed GitLab guide.

Full guide: GitStream for GitLab — Installation Guide

Bitbucket Cloud

Time: 10–15 minutes  |  Difficulty: ⭐⭐ Medium

High-level flow:

  1. Create a Bitbucket OAuth Consumer.
  2. Copy the Client ID and Secret into LinearB under gitStream.
  3. Authorize LinearB to access the workspace.
  4. Add webhooks for the repositories you want to automate.

Full guide: GitStream for Bitbucket Cloud — Installation Guide

Essentials Plan — Managed Mode & Optional YAML

Time: 1–3 minutes  |  Difficulty: ⭐ Very Easy

Where to configure:
Go to Company Settings → AI Tools.

1. Enable Managed Mode (Essentials only)

  1. Navigate to Company Settings → AI Tools.
  2. Select Managed Mode as the execution mode.
  3. Toggle on the automations you want (e.g., AI Review, AI Description, Co-author labels, ETR labels, Dependabot approvals).

Managed Mode uses LinearB’s managed runner. No YAML or CI changes are required.

Full Essentials setup guide: Install gitStream entirely from the LinearB Platform

2. (Optional) Use Self-Managed Mode with YAML

If you prefer full control, you can switch to Self-Managed Mode and configure gitStream via YAML files in your repositories (.cm). Use the starter YAML below as a low-noise baseline.


Low-Noise YAML Starter (GitHub / GitLab / BitBucket)

Use this starter when running in Self-Managed Mode on GitHub or GitLab. It focuses on low-noise, high-signal PR automation: AI review, AI description,

Note: Treat this as a conceptual starter. Your production configuration should follow your internal standards, risk appetite, and existing gitStream conventions.


Explore automations available to you

Once gitStream is installed, you can layer in more automations to reduce toil and improve consistency:

  • Reviewer assignment based on expertise (paths, services, or ownership).
  • Fast-track PRs that are small, low-risk, or docs-only.
  • Enforce commit or branch naming conventions.
  • Standardize PR templates and required metadata.
  • Deeper AI-based review rules for security, performance, or maintainability.

Recommended next reads:

  • giStream Automation Library
  • Tip: Start with 1–2 high-value automations, validate the impact with a pilot team, then roll out to more repos.


    Troubleshooting

    No automations are firing on PRs
    • Confirm gitStream is installed and connected for your Git provider (see provider section above).
    • For Self-Managed Mode (Essentials or Enterprise plan), verify:
      • Your YAML files are in the default branch under .cm/.
      • The on: triggers (e.g., pr_created, commit, pr_ready_for_review) match the events you expect.
      • There is no if: condition that always evaluates to false (for example, restricting to a branch that is not used).
    • For Managed Mode (Essentials only), check that:
      • Managed Mode is selected under Company Settings → AI Tools.
      • The specific automations (AI Review, AI Description, etc.) are toggled ON.
    • Confirm webhooks or app events are successfully reaching LinearB (no 4xx/5xx errors in your Git provider’s webhook logs).
    AI description is not updating the PR body
    • Make sure the describe-changes@v1 action exists in your YAML and is under an automation whose triggers run on PR creation or commits.
    • Verify concat_mode: append (or your chosen mode) is configured correctly.
    • Check that the PR is not marked as draft if your if: clause excludes drafts.
    • Ensure the gitStream app/token has permission to update PRs in your Git provider.
    Labels are not appearing on PRs
    • Confirm the automation uses add-label@v1 or add-labels@v1 with valid label names.
    • Check that you are on a provider that supports labels:
      • GitHub / GitLab: labels supported.
      • Bitbucket Cloud: labels on PRs are not supported; label-based actions will not apply.
    • Verify the app/token has permission to manage labels.
    • Check when: conditions on the label actions (for example, unresolved threads, missing Jira) are actually true for the PR being tested.
    Reviewers are not being assigned
    • Confirm the YAML uses add-reviewers@v1 and that who.experts (or your reviewer list) is defined in the config section.
    • Ensure gitStream has permission to request reviewers in your Git provider.
    • Check that the PR author is not listed as a reviewer (some providers ignore self-assignment).
    • Verify the automation’s if: conditions are met (for example, not a bot, not a draft).
    The “low-noise” mono-comment is missing or duplicated
    • Confirm your YAML has a single add-comment@v1 action and that no other automations are also posting summary comments.
    • Make sure you’re not using conflicting rules that run on overlapping triggers (e.g., multiple automations with pr_created + commit both adding comments).
    • If you recently changed the comment template, test on a new PR to ensure old comments are not being confused with the new format.
    Need more help?

    If you’ve confirmed installation, webhooks, and YAML but gitStream still isn’t behaving as expected, please contact LinearB Support with:

    How did we do?

    gitStream - Managed Mode (Essentials Plan)

    Contact