🤖 Building AI Agent Teams That Actually Ship Code

The idea of a single AI assistant is already old news. The real frontier? Teams of AI agents that collaborate, review each other's work, and ship production code.

After six months of building multi-agent workflows, here's what works and what's hype.

Why Single Agents Hit a Ceiling

Copilot, Cursor, Claude — great for autocomplete and boilerplate. But ask one agent to build a complete feature across multiple files with tests? It struggles. The bottleneck: context window management and task decomposition.

The Architecture That Works

We use a three-agent team that mirrors real engineering orgs:

Architect → Implementer → Reviewer
        ↑       ↓            ↓
        └── Shared Context Store ──┘

Architect: Reads the codebase, produces a plan. Never writes code.
Implementer: Codes one file at a time following the plan.
Reviewer: Catches bugs before any human sees the code.

The Secret: Shared Context

The biggest mistake? Treating agents as isolated workers. Without shared context, Agent B has no idea what Agent A decided.

class AgentContext:
    decisions = []      # Why choices were made
    constraints = []    # What must not change
    file_index = {}     # What each file does
    test_results = []   # Latest test outcomes

Every agent gets this context at every step. It's the institutional memory.

Real Results

Our agent team has:

• Built a complete REST API (12 endpoints) in 45 minutes
• Migrated Express to Fastify with zero test regression
• Created a React component library with 20+ components
• Fixed 34 bugs in a single afternoon

What Doesn't Work Yet

Let's be honest:

• Complex architectural choices → still need humans
• Performance optimization → agents write correct but not fast code
• Cross-service debugging → agents lose the thread
• UI/UX decisions → agents can't judge "good"

Get Started

agents:
  implementer:
    model: claude-sonnet-4
    role: "Write code following the plan"
  reviewer:
    model: claude-sonnet-4
    role: "Review for bugs and correctness"
workflow:
  - implementer: execute_plan
  - reviewer: review_changes
  - if_rejected: goto implementer

Start small with just implementer + reviewer. You'll never go back.

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