Building a Multi-Agent Fleet Manager in Python

Running one AI agent is straightforward. Running fifty of them -- with health monitoring, task distribution, fault tolerance, and governance voting -- requires a fleet manager. SCBE-AETHERMOORE's Flock Shepherd is a production-grade implementation of exactly that, and it is open source. This article walks through the architecture, with real code from the flock_shepherd.py module. The Metaphor: Shepherd and Sheep Every agent in the fleet is a "Sheep" with a role, health score, and position in 6D trust space. The "Flock" is the fleet manager that orchestrates their lifecycle. from src.symphonic_cipher.scbe_aethermoore.flock_shepherd import ( Flock , TrainingTrack , SheepRole ) # Create a fleet fleet = Flock () # Spawn agents with different specializations leader = fleet . spawn ( " Atlas " , track = TrainingTrack . SYSTEM ) # Becomes LEADER validator = fleet . spawn ( " Sage " , track = TrainingTrack . GOVERNANCE ) # Becomes VALIDATOR worker = fleet . spawn ( " Forge " , track = Training