When AI Fallback Works Technically but Fails Editorially
Many teams add model fallback and celebrate uptime, but tone and teaching style drift badly between providers. If readers can detect model switches, your content system is not production-ready yet.
Step 1: Define style constraints as machine-checkable rules
style:
max_passive_voice_ratio: 0.12
forbidden_phrases:
- "in conclusion"
- "final teaching note"
required_structure:
- motivation
- steps
- pitfalls
Step 2: Score each draft before publish
def score_style(draft, rules):
score = 100
for phrase in rules["forbidden_phrases"]:
if phrase.lower() in draft.lower():
score -= 25
return max(score, 0)