I Built a Coding Agent That Fixes GitHub Issues - in just a few lines of code

I built a coding agent that picks up GitHub issues, writes the fix in a sandbox, and pings me on Slack when the PR is ready for approval - without writing a single line of Docker, Slack or state management code. Here’s how.

The Workflow

A new GitHub issue triggers the workflow. The agent comments on the issue, clones the repo into a sandboxed Docker container.

Two agents take over - planner and coder. Both get built-in sandbox tools automatically: shell execution, file read/write, edit, glob, grep, web search. I just defined the agent goals. Polos handled the sandbox lifecycle, tool wiring, and coordination.

The coder finishes. The workflow pauses for human review. I get a Slack notification, review the diff, approve, PR is live.

const sandbox = sandboxTools({
  env: 'docker',
  scope: 'session',
  docker: { image: 'node:20-slim', memory: '2g' },
});

const planner = defineAgent({
  id: 'planner',
  model: anthropic('claude-sonnet-4-5'),
  systemPrompt: 'Analyze the issue and create an execution plan.',
  tools: [...sandbox],
});

const coder = defineAgent({
  id: 'coder',
  model: anthropic('claude-sonnet-4-5'),
  systemPrompt: 'Implement the plan. Read, write, and test code.',
  tools: [...sandbox],
});

I didn’t have to figure out how to create the Docker container, execute commands inside it, manage file system access, or keep the same sandbox alive across multiple tool calls within a session. Polos manages the full sandbox lifecycle - creation, tool execution, persistence across calls, and cleanup.

Full working example: Typescript | Python

Demo

3-minute video:

For this demo, I used a fork of the Zod repo and gave the agent an existing issue. Within seconds it commented on the issue, started working in the sandbox. A few minutes later, Slack notification - coder finished, ready for review. Approved from my phone. PR was live.

What I Used

I built this with Polos, an open-source runtime for AI agents. What I got out of the box:

• Sandboxed execution - agents run inside managed Docker containers with built-in tools for shell, files, and web search

• Slack integration - @mention agents, get responses in thread, receive notifications when agents need input

• Durable workflows - agent fails at step 47 of 50, resumes from 47

• Observability - OpenTelemetry tracing for every tool call and decision

• LLM agnostic - any provider via Vercel AI SDK and LiteLLM

curl -fsSL https://install.polos.dev/install.sh | bash
npx create-polos
cd my-project && polos dev

Github repo: https://github.com/polos-dev/polos

100% open source. Python and TypeScript.

If you’re building agents that do real work, run commands, touch real systems - give it a try. I’d love to hear what you build.