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Linear

Project Management

Linear is the issue tracker product and engineering teams actually want to use. Built for speed, keyboard-first, and now wired for AI agents that work alongside humans on the same issues, projects, and cycles.

Linear is what engineering teams pick when they finally give up on Jira. It is fast, opinionated, and built keyboard-first. The interesting part for operators is what has happened to Linear in the last 18 months: it stopped being a tracker and started becoming the substrate AI agents use to actually ship code.

What Linear Does

Linear organises product work into issues, cycles, projects, and initiatives. Every layer is connected, so a customer request can map all the way up to a quarterly initiative without anyone copy-pasting between tools. The platform is structured around five stages that mirror how product teams actually operate.

  • Intake. Customer messages, support tickets, and feedback convert into routed issues via Asks and Customer Requests.
  • Plan. Roadmaps, initiatives, PRDs, and visual planning for what ships in the next cycle or quarter.
  • Build. Issue management with sub-issues, dependencies, sprints (called cycles), and direct AI agent delegation.
  • Diffs. Code review built into Linear, with structural diffs designed for both human and agent-authored pull requests.
  • Monitor. Insights dashboards, Pulse updates, and cycle reports that surface where work actually stalls.
  • Mobile, desktop, and CLI. Same shortcuts, same speed, same data model across every surface.

Linear's AI Agent Platform

Linear treats AI agents as actual workspace members. You add Cursor, Codex, Devin, Factory, or your own custom agent the same way you'd add a teammate. They get assigned issues, mentioned in comments, and they ship pull requests back to Linear. The human stays the primary assignee, the agent shows up as a contributor, and everything they do is visible in the issue timeline. That accountability model is the reason this works at mid-market scale and not just at hobbyist demos.

Automations We Build with Linear

Linear out of the box is a great tracker. Linear with the right automations around it becomes the operating system for an engineering org. Here is what we typically wire up for mid-market product teams.

  • Intercom and Zendesk customer requests converted into Linear issues with conversation context, sentiment, and ARR attached, so product can weight requests by revenue impact.
  • Sentry and PagerDuty alerts auto-routed into Linear, tagged by service ownership, with stack traces in the issue description and on-call notified in the right Slack channel.
  • Weekly cycle reports generated by a script reading the Linear API, posted to Slack and emailed to leadership. No engineer has to write the update.
  • PR routing automations that read Linear labels and assign reviewers based on code ownership rather than round-robin.
  • Customer-facing changelog generated from Linear issues marked Public, auto-published to a status page or Slab doc when a cycle closes.
  • Bug triage agent (Sentry Seer, or a custom one) that examines new issues, suggests root cause, and tags the right team before a human looks at it.
  • Sprint planning data pulled from Linear into Notion or Coda dashboards for CTOs and VPs who want a single weekly view across all squads.

Why Teams Choose Linear

  • Speed. Every interaction is keyboard-driven and sub-100ms. Engineers stop avoiding the tracker because using it costs them nothing.
  • Opinionated defaults. Cycles, statuses, and labels are designed around how shipping teams actually operate, so the setup time is hours not weeks.
  • AI-native architecture. Agents are first-class workspace members with audit trails, not bolted-on chatbots.
  • A real API. The Linear GraphQL API is one of the cleanest in SaaS, so custom automations and dashboards are genuinely buildable.
  • Used by serious product teams. OpenAI runs 3,000+ users on Linear. Vercel, Ramp, Cursor, Mercury, and Brex all run on it. That tells you what the ceiling looks like.

Linear integrates natively with GitHub, GitLab, Slack, Figma, Sentry, Intercom, Zendesk, Notion, and Zapier, and supports custom AI agents through its API and MCP server. Pricing runs from a free tier (250 issues, 2 teams) up through Basic at $10 per user per month and Business at $16 per user per month billed annually, with custom Enterprise pricing for SAML, SCIM, and granular admin controls. That is the platform. The build we do is everything that sits around it, turning Linear from an issue tracker into the engineering operating system.

Use cases

Engineering Cycle Operations

We set up Linear as the single system of record for engineering cycles. Triage rules, cycle templates, and project rollups so leadership sees real velocity, not a Jira dashboard nobody trusts.

Customer Request Capture

Intercom, Zendesk, and Slack messages convert into Linear issues with full customer context attached. Product gets one queue of weighted requests, support stops chasing engineers in DMs.

Incident and Bug Routing

Sentry and PagerDuty alerts auto-create Linear issues tagged by service and severity, routed to the right team. On-call stops being a paste-the-stacktrace-into-Slack ritual.

AI Agent Delegation

Bug triage agents, PR review agents, and code-writing agents (Cursor, Codex, Devin) assigned to Linear issues as full workspace members. Humans stay primary, agents do the legwork.

Cross-Team Visibility

Cycle reports auto-publish to Slack each Friday. Roadmap initiatives sync to Notion or Slab so non-engineering stakeholders see status without joining the engineering workspace.

Industries we automate this for

Ready to automate Linear?

Tell us what you need and we'll show you exactly how we'd connect Linear to the rest of your stack.

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