What stood out to me here is the focus on silent failures rather than obvious crashes. An automation can look perfectly healthy from its logs while doing nothing useful, which is a much harder problem to catch in production. This is especially relevant when building AI powered workflows at Oglas AI we’ve found that observability, validation, and reliable failure handling matter just as much as the automation itself.