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Use Cases/Build an AI Agent Team for Project Delivery

Build an AI Agent Team for Project Delivery

Use Squad to orchestrate specialized AI agents that collaborate on full project delivery with defined roles and handoffs.

Development#agents#multi-agent#orchestration#collaboration#squad
Works with:claude-codeopenai-codexgemini-clicursor
squad-agents
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The Problem

You are a solo founder or small team with a full requirements doc but no specialists. You need an architect, developer, reviewer, QA engineer, and PM — but hiring takes months. Running one AI agent at a time is slow and loses context between sessions.

The Solution

Use Squad to create a team of specialized AI agents, each with a defined role, private context, and structured handoff protocol. They communicate through shared files in .squad/, persist knowledge across sessions, and coordinate through GitHub issues.

Step-by-Step Walkthrough

Step 1: Initialize Squad

bash
cd ~/projects/invoice-app
npm init -y && git init
npm install -g @bradygaster/squad-cli
squad init
gh auth login

Step 2: Launch and Describe the Project

bash
copilot --agent squad --yolo

Prompt: "Build an invoice management SaaS. I need user auth with Google OAuth, CRUD for invoices with PDF generation, Stripe billing for Pro plan, and a dashboard showing revenue metrics. Tech stack: Next.js, PostgreSQL, Tailwind."

Squad generates team members with thematic names. Confirm with yes.

Step 3: Let the Team Work

Squad's Lead agent breaks the project into GitHub issues and assigns them to team members:

  • Lead creates architecture decision records in .squad/decisions/
  • Backend builds API routes, database models, and auth
  • Frontend picks up handoff docs and builds UI components
  • Tester writes tests against completed endpoints

Step 4: Monitor and Merge

bash
squad status        # See what each agent is working on
squad triage        # Auto-assign new issues to appropriate agents

Review completed work, merge PRs, and let the team continue on the next batch.

Real-World Example

Kai, a solo founder, uses Squad to build an invoice management MVP. He runs squad init and describes the project. Squad creates 4 agents: Ledger (Lead/Architect), Scribe (Backend), Canvas (Frontend), and Auditor (Tester). Ledger writes a decision record choosing PostgreSQL over MongoDB for relational invoice data. Scribe builds the API and writes a handoff: POST /api/invoices accepts {client_id, items[], due_date} with JWT auth. Canvas picks up the handoff and builds the invoice form with Tailwind. Auditor writes Jest tests for the API and Playwright E2E tests for the form flow. After 3 days of iteration, Kai has a working MVP with auth, invoice CRUD, PDF export, and 47 passing tests — work that would have taken a solo developer 2-3 weeks.

Related Skills

  • squad-agents — The framework for building AI agent teams