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Why usage matters

Workflow Machine tracks usage so you can understand how much automation work your workspace is consuming over time. This is useful for planning, troubleshooting, and keeping important workflows within the limits of your current Subscription plan.

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Two kinds of usage to watch

The two main usage categories are:
  • Run credits
  • AI credits
These measure different parts of workflow activity.

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Run credits

Run credits reflect workflow execution volume. In the current product model, every 10 workflow steps count as 1 run credit. That means a longer workflow can consume more credits than a shorter one, even if both are triggered the same number of times. Examples:
  • 1 step = 1 run credit
  • 10 steps = 1 run credit
  • 11 steps = 2 run credits
This is worth keeping in mind when designing workflows with:
  • many repeated steps
  • unnecessary branching
  • extra processing that does not change the outcome
Simple workflows are not just easier to maintain. They are usually more efficient too.

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AI credits

AI credits track the parts of the product that rely on AI generation or processing. If your workflows use AI steps for summarization, extraction, drafting, or classification, those workflows will usually affect AI credit usage in addition to run credits. All chat messages also count toward AI credit usage. If you use your own AI connections with providers such as OpenAI, Anthropic, or Gemini, AI credits are not consumed for that provider usage because the model calls are billed through your own API key instead. The more often an AI step runs, the more important it becomes to monitor usage and make sure the step is actually adding value.

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How to design with usage in mind

You do not need to optimize every workflow immediately, but a few habits help:
  • keep your first version small
  • avoid unnecessary steps
  • use AI only where it improves the result
  • test before publishing so failed runs do not waste repeated execution
  • review run history to spot workflows that trigger too often
Usage awareness is not about making workflows minimal at all costs. It is about making them intentional.

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Where to check usage

Usage information is available in the product Subscription page. That is where you can review how many run credits and AI credits have been used relative to your plan. If a workflow is running more often than expected, usage data is one of the fastest ways to notice it.

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A practical way to think about credits

Use this mental model:
  • Run credits measure how much workflow execution is happening
  • AI credits measure how much AI work is happening inside those workflows
If a workflow becomes expensive in either category, it is often a sign that the trigger frequency, step count, or AI usage pattern should be reviewed.