AI Project Manager
The AI Project Manager is a fully-integrated AI project manager built for enterprises, operating inside Slack to manage tasks, sprints, and projects in Linear through natural language.
“@AI Project Manager can you assign Gokhan to fix the 500 error in onboarding by Friday?”
Executive Summary
The AI Project Manager is a fully-integrated AI project manager built for enterprises, operating inside Slack to manage tasks, sprints, and projects in Linear through natural language. It handles complete workflows—from parsing a message like "@AI Project Manager can you assign Gokhan to fix the 500 error in onboarding by Friday?" to automatically creating a task titled "Fix 500 error during onboarding flow," setting priority based on urgency cues, assigning it to Gokhan, attaching the Slack thread for context, and adding it to the current sprint—while enforcing best practices like cycle-based planning, minimal viable descriptions, and automated Slack confirmations with interactive task controls.
Specific Workflow
Monday morning, Engineering Manager Emma notices a critical bug in the onboarding flow. Rather than switching contexts to Linear, she types in the team's Slack channel: '@AI Project Manager create a high-priority task to fix the 500 error when new users complete step 3 of onboarding. Assign to Priya and make sure it's in this sprint. We need this fixed by Wednesday.' Within seconds, AI Project Manager parses her request, recognizing the urgency keywords and deadline. It creates a properly formatted task in Linear titled 'Fix 500 error in step 3 of user onboarding flow', sets priority to 'High', assigns it to Priya, adds it to the current sprint, sets a due date of Wednesday, and tags it with appropriate labels including 'bug' and 'onboarding'.
The agent then posts back in Slack with a confirmation: 'Created high-priority task LIN-437: Fix 500 error in step 3 of user onboarding flow. Assigned to Priya with deadline Wednesday in current sprint (Sprint 23). View task: [link]'. The message includes interactive buttons for quick actions like 'Modify', 'Add Details', or 'Change Priority'.
When Priya sees the notification, she clicks the link, reviews the task, and begins working.
As she makes progress, she comments directly in Slack: '@AI Project Manager update LIN-437 – identified the issue, it's a database timeout. Will have a fix ready for review by EOD.' AI Project Manager updates the task description with this context and changes the status to 'In Progress'. It also schedules an automatic reminder for end of day to check if Priya has submitted the fix for review. The entire workflow happens seamlessly through natural language in Slack, eliminating context switching while maintaining complete, structured data in Linear.
Enforced Best Practices
- 1Structured Task Creation: Automatically formats vague requests into proper task titles, enforcing a consistent pattern of [Action] + [Object] + [Context] to improve scanability and clarity.
- 2Required Fields Completion: Ensures critical fields like assignee, priority, and sprint are always populated, prompting for missing information when needed.
- 3Cycle-based Planning: Maintains sprint integrity by preventing overloading, warning when a sprint exceeds 85% of historical velocity.
- 4Dependency Management: Automatically detects and links dependent tasks mentioned in conversation contexts.
- 5Contextual Attachments: Preserves discussions by attaching relevant Slack threads to tasks for future reference.
- 6Status Synchronization: Keeps Slack and Linear in sync, reflecting real-time status updates in both platforms.
- 7Deadline Enforcement: Proactively sends reminders as deadlines approach and highlights at-risk tasks in daily standups.
- 8Historical Knowledge Application: Suggests appropriate assignees and estimates based on similar past tasks.
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