Multi-agent systems fail when they hit a tool-call loop. Orchestration is just distributed systems engineering. Stop chasing autonomy. If you cannot trace state transitions between agents, you are waiting for a production incident your logs cannot explain
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Multi-agent systems look great in demos until they hit infinite tool-call loops. Without circuit breakers, they are just expensive, flaky microservices. Stop treating them like magic. Build for real-world failures, not slide deck fantasies.
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Scaling multi-agent systems is hard. I’ve seen agents trigger infinite tool-call loops that tank latency. If you're moving to production, you need failure patterns. I’m sharing how we keep agents stable in the wild
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Multi-agent systems look great in a notebook, but reality hits when you ship. I’m breaking down the trade-offs of running these workflows at scale, specifically managing tight latency budgets across model hops
**Snippet (234 characters):** Multi-agent AI is great until you hit recursive tool-call loops that rack up costs
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We’ve all seen the demos where agents chain perfectly, but production is a different beast. I’m diving into the messy reality of multi-agent workflows—specifically, how to stop runaway tool-call loops before they incinerate your latency budget