How do you Mapout AI workflows when one suddenly costs 2× more than usual?
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After talking to a few teams building AI products, one pattern keeps coming up. Cost spikes are usually easy to notice, but understanding why they happened is much harder. Some examples I've heard: retries after failures repeated tool calls long-running workflows context growing over multiple steps Most people mentioned looking through logs or traces to reconstruct what happened. I'm curious how your team approaches this today. If an AI workflow suddenly became twice as expensive as norm
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