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Design and set up a production-ready CUA workflow — from task definition to execution environment and monitoring.
Read through the lesson, mark it complete when the concept is clear, then move to the next lesson in the sequence or jump back to the module map.
Before building a CUA workflow, establish:
Vague tasks produce unreliable results. Every ambiguity in the task definition is a potential failure point.
| Environment | Pros | Cons |
|---|---|---|
| Local machine | Full access, no extra cost | Disrupts your workspace |
| Virtual machine | Isolated, safe | Setup overhead |
| Cloud browser | Scalable, monitored | Cost, network-limited |
| Docker container | Reproducible | Requires setup |
For most production use, a cloud browser environment is safest — it's isolated from your production systems and can be destroyed and recreated easily.
Treat CUA instructions like operator instructions for a new employee:
Task: Collect competitor pricing from these 5 websites: [list]
For each site:
Output: A CSV with columns: site, plan_name, price, billing_period, currency
If you can't find pricing on a site, note it as "pricing not public" rather than guessing.
For long tasks, build in checkpoints where the agent saves progress:
After completing each site, save the partial data. If the agent fails on site 4, it can resume from site 4 rather than starting over.
Production CUA workflows should log:
This audit trail is essential for debugging failures and improving reliability.