I feel like most AI workflows can be solved pretty effectively by a single capable LLM or with upto 5 subagents however, many engineering teams are focused on multi-agent architectures at huge scales.
Curious to understand exactly when it becomes worth it / what production use cases there are for large multi-agent swarms: I’m trying to understand exactly where that value lies.
If you are run agent swarms in production: what is the main use case / need and what is your biggest pain point right now (state sync, token costs, cascading failures, latency)?
[As context: I am a founder at Acyclic Labs (YC F26) and we are building infra to scale agents. Looking to map out when the swarms are actually justified and when they are wasteful!]
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