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Automate Software Development with an AI Agent Manager using OpenAI Symphony and Linear

Set up a cloud-based 'software factory' where AI agents autonomously handle coding tasks assigned and managed through a Linear project board. This workflow turns you from a coder into an AI agent manager.

Automate Software Development with an AI Agent Manager using OpenAI Symphony and Linear

From 02:24 to 18:05, Alessio Fanelli demonstrates an agent-manager workflow that pulls work from Linear, runs coding agents, and returns pull requests and previews. Clip range: 02:24 to 18:05.

Before you start

What you need

  • Cloud VPS with persistent internet access
  • Installed OpenAI Symphony framework
  • Linear workspace with workflow columns configured
  • GitHub repository with PR creation permission
  • Vercel account for preview deployments

What you’ll make

A GitHub pull request linked to a Linear issue with a deployed Vercel preview and agent-generated implementation changes.

Tools used

Step by step

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

7 steps

Step01

Set Up Your Infrastructure

Set up a dedicated cloud VPS (Virtual Private Server) as an always-on environment for your agents. On this server, install and configure OpenAI's open source Symphony framework.

Step02

Create and Assign a Task

On your Linear project board, create a new issue. Describe the coding task in natural language, just as you would for a human developer.

Example prompt
clean up, pretty stable. let's remove the spread column too noisy. Let's also make the that name.
Step03

Trigger the AI Agent

Drag the new Linear issue from your backlog into the 'To Do' column. This action triggers Symphony, which monitors this column, to assign an AI agent to the task.

Step04

Agent Planning and Execution

The agent begins by creating a detailed plan, or 'workpad,' outlining acceptance criteria and validation steps. It then executes the plan, writing and modifying the necessary code.

Step05

Receive Work for Human Review

When the agent finishes its initial work, it opens a pull request (PR) in GitHub, deploys a live preview on Vercel, and moves the Linear ticket to the 'Human Review' column. This signals the task is ready for your inspection.

Step06

Initiate the Rework Loop (If Necessary)

If the code requires changes, leave specific comments on the GitHub PR. Then, move the Linear ticket to the 'Rework' column. The agent will read your feedback, turn it into a checklist, address each point, and submit an updated PR for another review.

Example prompt
In [file_name.js], the new function is missing error handling for null inputs. Please add a check and return an appropriate error. Also, the variable name `temp_val` is unclear; rename it to `user_id` for clarity.
Step07

Complete the Task

When you are satisfied with the changes, approve and merge the pull request in GitHub. The agent will detect the merge and automatically move the corresponding Linear ticket to the 'Done' column.

What good looks like

  • Moving a Linear issue to To Do triggers agent execution
  • Agent creates a workpad with acceptance criteria and validation steps
  • GitHub pull request is opened with code changes tied to the issue
  • Vercel preview URL is attached to the pull request

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After the steps

Runbook notes

How to recover when the loop fails and where human judgment helps.

Recover

If it goes sideways

Symphony does not detect Linear status changes
Verify Linear webhook configuration and API token scopes
Preview deployment fails on Vercel
Check environment variables and build logs before requesting review
Agent rework ignores reviewer comments
Require checklist extraction from each unresolved GitHub review comment

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