We’ve been exploring autonomous AI teams to handle some of our end-to-end processes. The idea is solid: one agent handles data analysis, another generates reports, another sends notifications. It’s like having a team that operates 24/7 without breaks or mistakes.
But when I try to model the cost, I’m running into a problem. Each agent interaction isn’t free. If we’re running five agents on one process, and they’re making API calls to multiple models, running data transformations, and potentially correcting each other’s work—where does the billing actually spike?
From the retrieved context, I can see that autonomous decision-making and multi-step reasoning are where AI agents excel. But that also sounds like where costs could get out of hand if you’re not careful. One agent might trigger another, which triggers a third, and suddenly you’re burning through a lot of compute.
I’m also wondering about coordination overhead. If these agents are supposed to work together, is there a cost to that handoff process? Are we paying for validation and error correction when one agent flags something another agent missed?
How do you actually keep costs predictable when you’re running multiple autonomous agents on a single workflow? What’s your budget model look like?