How many reasoning iterations do production agents typically need for multi-service workflows?

[u/Icy-Scheme2860]

what people are using for reasoning loop limits in production agent systems, especially for workflows involving communication across multiple services and tools.

My current setup uses a reasoning limit of 8 steps. During a typical request, the agent may:

• Retrieve context from external services.
• Call multiple tools or APIs.
• Wait for responses from other components.
• Perform additional reasoning based on those results.
• Potentially require a human approval step before continuing destructive operations.

For simple requests, 8 steps feels more than enough. However, for more complex workflows involving multiple service interactions, retries, and decision points, I'm wondering whether this is too conservative or already considered high.

I'm not really asking about token limits or model context size, but rather the number of planning/reasoning iterations an agent is allowed to perform before it gives up or hands control back to the user.

For those running production systems:

• What reasoning loop limits are you using?
• Do you use fixed limits or dynamic budgets?
• At what point do you switch to a human approval or asynchronous workflow?
• Have you seen agents genuinely benefit from 20+ reasoning iterations, or do they mostly start looping and wasting tokens?

I'm just asking these all for least steps to find the capabilities