Event-driven multi-agent architecture beat model routing on cost, 32-agent finance system shows
tradfyAi · reddit · 2026-09-16
In a real-time financial-market system of 32 specialized agents across GPT-5.6 Sol, Fable, Opus and other models, the author found switching from manually triggered workflows to a genuinely event-driven architecture cut costs dramatically while improving quality. Small models handle classification, extraction, routing and summaries; outputs with timestamps and evidence go into a graph-based shared context layer; a "council" of frontier models periodically reviews, compresses and snapshots the context. Open problems remain: stale context, contamination by bad observations, hallucination on thin evidence, and lossy periodic compression. The core lesson: the biggest cost driver was repeatedly feeding unstructured context to expensive models, not model choice.
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