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 normal, what's your investigation process?
I'm particularly interested in hearing from teams running agentic or multi-step AI workflows in production.
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