Ask HN: Multi-agent workflows in production; Where people using 1000s of agents?

Acyclic Labs founder, whose company is in the Y Combinator F26 batch, posted an Ask HN thread asking production teams to describe when multi-agent AI architectures at the scale of thousands of agents are actually justified, versus when a single capable LLM or up to five subagents suffices. The founder said Acyclic Labs is building infrastructure to scale agents and wants to map the use cases and pain points — state sync, token costs, cascading failures, and latency — that drive large agent swarms in production. The thread had 1 point and 0 comments at the time of the post.

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 Comments URL: https://news.ycombinator.com/item?id=49689454 https://news.ycombinator.com/item?id=49689454 Points: 1 Comments: 0