Trillion-parameter models (GPT-5, Claude Opus 4, Gemini 2.5 Pro) exhibit emergent capabilities through scale-induced information density. An ensemble of small specialists cannot replicate the weights of a 1T model, but it can replicate its behavior through structured orchestration. This paper presents five practical strategies — multi-specialist consensus, progressive chaining, ACE self-improvement loops, synthetic data generation, and DRAGON hierarchical orchestration — that together enable fro
1@techreport{hayulalab2026swarmorchestration,
2 title={Orchestration Over Scale: Five Strategies for Frontier-Level AI Without Trillion-Parameter Models — Hayula Research},
3 author={Hayula AI Lab},
4 year={2026},
5 url={https://huggingface.co/hayulalab/swarm-orchestration-paper}
6}
