BYOBot

Automate Your Linear Workflows with AI

Linear keeps your issues clean, but someone still has to review every cycle, triage the incoming queue, write the release notes, and post the roadmap digest to Slack. Describe what you do in Linear each cycle: you'll receive a ready-to-use AI workflow automation. We'll guide you through testing it.

Describe the workflow you want to automate: we'll build you a step-by-step spec you can run today.

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Build Your Own Linear Bot

All you need to do is document the steps you take in Linear. We'll use your steps to create instructions for AI to take over your Linear tasks from now on.

1
Describe your Linear workflow

Walk us through what you do, which issues you triage, what cycle reports you pull, where digests and release notes go. Plain language, no technical jargon required.

2
We map it to an automation

BYOBot turns your description into your agent: a prompt for any AI chat tool, a browser agent script that runs it for you, and a full pipeline ready for a developer.

3
AI takes over your Linear tasks

You receive your agent, ready to use. Start in a chat tool to test the logic, go hands-free with a browser agent, or hand the pipeline spec to a developer to deploy.

Start Building Free โ†’

Works with your Linear stack

Pairs naturally with Jira GitHub

One agent for your Linear automations. Run it anywhere.

In your AI chat tool
Ready-to-use prompts for any AI chat tool

No setup. No code. Open Claude, paste the prompt, run your Linear workflow. Start here to validate the logic: paste in a list of cycle issues and confirm the output looks right.

Works with ChatGPT, Claude, Gemini, or any LLM: free to start
In a browser agent
An AI agent drives your browser for you

A browser agent prompt that opens your Linear board, reads the cycle data, and posts the digest to Slack on its own. Semi-automated, with you watching.

Works with any AI browser agent tool
In your stack
A full blueprint for unattended automation

An API-driven pipeline with Linear GraphQL API calls, data extraction logic, formatting rules, delivery scheduling, and error handling. Hand the spec to a developer or deploy it with an automation platform.

Connects to Zapier, Make, n8n, or custom APIs

What you get that an LLM alone won't give you

โœฆ Portable
Download it, use it with any browser-capable AI

A chat answer dies in the thread. Your agent is a file you own: run it in ChatGPT, Claude, or Gemini, drop it into a browser agent, or hand it to your stack, as many times as you like.

โœฆ Conversational
Training your AI agent is super easy

No prompt engineering degree required. Describe what you do, the tabs you open, the data you move, and BYOBot asks the questions that turn your knowledge into the spec.

โœฆ Tested
Custom QA milestones in every agent

Every build ships with smoke tests and pass, warn, and fail checks for each step. You'll know it ran right, not just that it ran.

See Yourself Using AI?

BYOBot can help automate Linear workflows for all of these roles, regardless of your experience or skill level.

Engineering Manager Engineering Product Manager Product
Tech Lead Engineering
Scrum Master Agile
DevOps Engineer Engineering
Startup Founder Leadership
CTO Leadership
Product Designer Design
QA Engineer Engineering
Technical Program Manager Engineering

Your Linear workflows, automated by AI

Linear is built for speed, but a surprising share of the time spent around it isn't shipping: it's reporting. Pulling cycle velocity into a digest. Triaging the incoming issue queue. Writing release notes from a column of completed tickets. None of that is hard. It's just repetitive. BYOBot is an AI workflow automation tool that maps those Linear loops into structured specs. Describe what you do in Linear each cycle. Get a runbook back.

Every BYOBot build produces one portable agent with three ways to run it. The copy-paste prompt works in any AI chat tool: validate the logic in minutes, no setup. For a Linear workflow, that might mean pasting a list of cycle issues and getting a formatted completion summary back immediately. The browser agent navigates to your Linear board, reads the data, and posts the digest to Slack on its own. And the pipeline spec includes GraphQL API calls, webhook triggers, and a QA checklist: ready to hand to a developer or deploy with an automation platform. Start with the chat prompt to confirm the logic. Move up when you're confident.

Linear rarely lives in isolation. It connects upstream to GitHub pull requests and downstream to Slack channels, Notion roadmaps, and Sentry error tracking. BYOBot maps automations that span this stack: pulling completed issues into release notes, syncing cycle status to a Notion tracker, triggering a PagerDuty alert when a high-priority issue stalls. If you can describe the loop, BYOBot can structure it. Explore more automation starting points at the AI Workflow Automation Starting Points hub.

Frequently Asked

Linear workflow automation means removing the manual steps that happen around your Linear board: the cycle reviews, the issue triaging, the roadmap digests, the cross-tool syncing that doesn't happen inside Linear itself. BYOBot maps those recurring loops into structured automation specs: a prompt you run in an AI chat tool, a browser agent that navigates Linear and connected tools for you, or a pipeline ready for a developer. The result is a runbook that replaces the copy-paste work without replacing the judgment calls.
Zapier is excellent at moving data between apps on a fixed trigger: if a Linear issue moves to Done, post to Slack. What it can't do is reason. If the issue data is sparse, the cycle has an unusual shape, or you need to decide which issues belong in the release notes, Zapier stops. BYOBot produces specs for agents that can evaluate what they find mid-run and adapt. Think of Zapier as the pipe and BYOBot as the routing diagram that figures out where the pipes should go.
The most common ones are cycle reporting (pulling completion rates, velocity, and cycle time into a formatted summary), issue triage (labelling and routing incoming issues to the right team and priority), Slack digests (posting a daily or weekly summary of open and closed issues to a channel), release notes (generating a changelog from completed issues in a cycle), and bulk updates (re-prioritizing, re-assigning, or closing a batch of issues based on criteria). If your workflow crosses into GitHub, Notion, Slack, or Sentry, BYOBot handles those transitions too.
BYOBot produces an automation spec, not a native integration. The prompt and browser agent versions run through the AI tools you already use: the browser agent navigates Linear the same way you do, using your existing session. The pipeline spec calls the Linear GraphQL API directly; it requires API credentials and a developer to implement or an automation platform to run. No app installation or OAuth connection is needed to get started.
No. The prompt and browser agent versions run entirely in the AI tools you already use: no setup, no credentials, no code. The pipeline spec that does require a developer to implement, but you'll have a detailed runbook to hand them rather than starting from scratch. Most Linear teams start with the chat prompt, validate the logic against a real cycle, then move to the browser agent for the actual browser automation.
For the browser agent, no special permissions are needed beyond your normal Linear access: browser agent navigates Linear as you, using your logged-in session. For the API pipeline, you'll need a Linear API key with read access to teams and issues, and write access to issue fields if you're updating them. The BYOBot spec will specify exactly which scopes are required and flag any steps that need elevated access.

Tell BYOBot what you do in Linear each week. Get an automation back in minutes.

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