CDX-201c · Module 3

Real-World Orchestration Examples

3 min read

Real-world multi-agent orchestration combines all the patterns: decomposition, parallel execution, hand-offs, context sharing, error recovery, and supervision. The key insight from production deployments is that simpler pipelines outperform complex ones. A two-agent pipeline (planner + implementer) that runs reliably beats a five-agent pipeline that fails 30% of the time due to coordination overhead.

Three production patterns have proven themselves across teams. The plan-implement-review pipeline: a three-agent sequential pipeline where each phase uses the optimal model. The parallel module pipeline: a fan-out pattern where independent modules are processed concurrently by identical agents. The triage-fix-validate pipeline: an event-driven pattern triggered by issues or CI failures that triages, proposes a fix, and validates the fix automatically.

# Production pattern: Plan-Implement-Review

┌──────────┐     ┌──────────────┐     ┌──────────┐
│ Planner  │────▶│ Implementer  │────▶│ Reviewer │
│ (o3)     │     │ (codex-1)    │     │ (o3)     │
└──────────┘     └──────────────┘     └──────────┘
    │                   │                   │
  plan.md          code changes        review.md
  decisions.json   test results        approved/rejected

# Production pattern: Parallel Modules

                ┌──────────────┐
           ┌───▶│ Agent (auth)  │───┐
┌────────┐ │    └──────────────┘   │  ┌─────────┐
│ Decomp │─┼───▶│ Agent (pay)   │───┼─▶│ Merge   │
└────────┘ │    └──────────────┘   │  └─────────┘
           └───▶│ Agent (users) │───┘
                └──────────────┘

Do This

  • Start with the simplest pipeline that solves your problem — usually 2-3 agents
  • Measure success rate and average duration for each pipeline pattern
  • Log everything — traces, hand-offs, failures, retries — for post-mortem analysis
  • Iterate on decomposition quality rather than adding more agents

Avoid This

  • Build a complex 5+ agent pipeline as your first multi-agent workflow
  • Optimize for speed before optimizing for reliability — correct output beats fast output
  • Deploy multi-agent pipelines to production without testing on representative tasks
  • Forget that every additional agent is an additional failure point — simplicity scales better