Integrating projects.do: Connect Your CI/CD Pipeline to an Autonomous PM

In modern software development, we live by automation. We write code, push it to a repository, and a sophisticated CI/CD pipeline takes over—building, testing, and deploying with precision and speed. Yet, for many teams, the moment the code goes live is when the automation stops and the manual "project management" work begins. Updating tickets, notifying stakeholders, and kicking off the next phase of a project often revert to emails, Slack messages, and manual card-dragging.

This is a fundamental disconnect. Our technical workflows are automated, but our business workflows are not. The result? Stale project boards, endless status meetings, and a frustrating gap between what the code is doing and what the project plan says is happening.

What if your project management system could be an active, intelligent participant in your CI/CD pipeline? What if, instead of being a passive system of record, it was an active system of execution?

This is the promise of Agentic Project Management with projects.do. By defining your projects as code and leveraging our API, you can connect your delivery pipeline directly to an autonomous Project Manager that executes workflows, manages dependencies, and keeps everyone in sync, automatically.

The Problem with Siloed Workflows

Traditional project management tools are fundamentally databases with a UI. They are great for recording what has happened or what is planned, but they require constant human intervention to stay accurate. This creates two separate, unsynchronized worlds:

1. The World of Code: Living in Git and executed by CI/CD pipelines. This is the ground truth of your product.
2. The World of Plans: Living in tools like Jira or Asana. This is a human-maintained representation of the product's progress.

The "sync" between these worlds is you. Developers have to remember to update tickets after a deployment. Product managers have to chase down engineers to get a real status update. This manual overhead isn't just tedious; it introduces delays and inaccuracies that ripple across the entire organization.

A New Paradigm: Projects-as-Code

projects.do flips the script. We believe your project plan shouldn't just be a description of the work; it should be executable code.

'Projects-as-Code' means defining your project plans, tasks, dependencies, and success criteria in a structured, machine-readable format. This allows our AI agents to interpret, automate, and execute the project workflow from start to finish.

import { Agent } from 'projects.do';

const projectAgent = new Agent();

// Define the project as a declarative spec
const newProject = await projectAgent.create({
  name: 'Q4 Product Launch',
  description: 'Coordinate all activities for the new feature launch.',
  owner: 'product.team@example.com',
  tasks: [
    { id: 'dev.deploy.feature', description: 'Deploy the new feature to production.' },
    { id: 'qa.run.smoke_tests', description: 'Run smoke tests in production.', dependencies: ['dev.deploy.feature'] },
    { id: 'marketing.send.announcement', description: 'Send launch announcement email.', dependencies: ['qa.run.smoke_tests'] }
  ]
});

// The agent is now actively managing this project
await projectAgent.start(newProject.id);

When a project is defined this way, it’s no longer a static checklist. It's a dynamic, stateful workflow waiting for triggers. And the most powerful triggers come directly from your development pipeline.

Bridging the Gap: A Practical CI/CD Integration

Because projects.do is API-first, you can make your CI/CD pipeline a first-class citizen in your project's lifecycle. Instead of the pipeline being the end of a task, it becomes the trigger for the projects.do agent to execute the next one.

Let's imagine our 'Q4 Product Launch' project. The first task is deploying the feature. We can configure our CI/CD pipeline (in this case, GitHub Actions) to notify projects.do upon a successful deployment.

Here’s what that looks like in a workflow file:

# .github/workflows/deployment.yml
name: Deploy and Update Project

on:
  push:
    branches:
      - main

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v3

      # ... your build, test, and deploy steps would go here ...
      - name: Simulate Deployment
        run: echo "Deployment successful!"

      - name: Notify projects.do
        if: success()
        run: |
          curl -X POST "https://api.projects.do/v1/projects/${{ secrets.PROJECTS_DO_PROJECT_ID }}/tasks/dev.deploy.feature/complete" \
          -H "Authorization: Bearer ${{ secrets.PROJECTS_DO_API_KEY }}" \
          -H "Content-Type: application/json" \
          -d '{
            "status": "completed",
            "metadata": {
              "commit_sha": "${{ github.sha }}",
              "run_url": "${{ github.server_url }}/${{ github.repository }}/actions/runs/${{ github.run_id }}"
            }
          }'

Let's break down what's happening in the Notify projects.do step:

1. Trigger: It only runs if the preceding deployment steps succeed (if: success()).
2. Action: It sends a secure API request (curl -X POST) to a projects.do endpoint.
3. Authentication: It uses secrets stored in GitHub to authenticate securely.
4. Payload: It tells the projects.do agent that the task dev.deploy.feature is now complete and even passes along useful metadata like the Git commit SHA and a link to the workflow run.

The moment this API call is made, the projects.do agent springs into action. It marks the deployment task as complete, sees that the qa.run.smoke_tests task's dependencies are now met, and could automatically trigger the QA team's testing suite, notify them on Slack, or assign the task in their queue.

No manual updates. No context switching. The project moves forward at the speed of code.

The Benefits of an Autonomous PM

Integrating your CI/CD pipeline with projects.do transforms your entire delivery process, creating a truly automated workflow from commit to value delivery.

• Real-Time Visibility: Your project status is never out of date. It is a direct reflection of the reality in your production environment.
• Zero Manual Overhead: Developers stay focused on writing code, not updating tickets. Project managers can focus on strategy, not status collection.
• Accelerated Delivery: By removing human latency between steps, the AI agent ensures the next phase of a project begins the instant the previous one is verifiably complete.
• True Business-as-Code: Your project plan and your CI/CD pipeline work in concert, creating a single, automated, and auditable system for delivering value to your customers.

Ready to stop managing projects and start executing them? Connect your pipeline to projects.do and let an autonomous agent handle the overhead.

Explore the projects.do API Documentation or Sign Up for a Demo to get started!