How to Engineer a Multi-Agent Pipeline for Production Reliability

We built a nine-agent pipeline that turns a natural language use case into working code, an interactive preview, and an implementation guide in under 4 minutes. It serves roughly 800 to 1,000 users per day, but its first production version consumed about 30,000 tokens and made 15 to 20 Pro-tier model calls per request. The useful lesson from this multi-agent AI implementation is not simply that…