Faithful Automator
The pipeline passed, what more do you need?
The Faithful Automator extends the same trust they give to any approved tooling to AI-generated output. If the model says the code is correct, the review is approved. If the AI-powered linter says no issues found, they ship with confidence. They rarely question the pipeline's outputs; they treat green dashboards as sufficient evidence.
Symptom
Vocabulary is diagnostic: 'the model flagged it,' 'the pipeline passed.' Treats AI-generated code reviews as equivalent to human reviews. Sets up automated AI-powered systems and then stops monitoring them. Dashboards show green across the board, always.
Why It Matters
The Faithful Automator's default trust creates a specific and devastating failure mode: silent degradation. Because nobody checks the AI's work, errors accumulate undetected. The gap between what the dashboards report and what the system actually does widens until a customer reports a bug every layer of the pipeline should have caught.
What the Chapter Gives You
How to institute random sampling of AI outputs as a mandatory process step, why calibration loops appeal to the Cleric's process-oriented nature, and the error-rate publishing that makes faith answer to evidence.
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