Dev Tools · 12h ago
Scaling AI Agent Systems: Lessons from a Pokémon-Themed Orchestrator
A developer expanded their personal AI orchestration system from 3 to 6 specialized agents, adding a capability registry to improve routing decisions. The shared journal grew to 240KB, consuming half the context window before tasks began. The system now uses a registry.json file and automated review pipelines to handle growing complexity.
Meridian48 take
The Pokémon analogy is fun, but the underlying challenges—agent routing ambiguity, context window bloat, and manual scaling—are real issues for anyone building multi-agent AI systems today.
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Scaling Your Pokémon Team: When Your AI System Outgrows Its Original Design →
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