AI Project Credibility: Why Honest Assessment Trumps Success Theatre

When AI projects hide technical challenges behind curated retrospectives, they sacrifice both developer credibility and useful feedback. This account exposes how sanitized metrics—and critical failures like cramming 118 backend services into a single file—reveal the cost of prioritizing appearance over transparency. Genuine stakeholder trust requires candid assessment of technical debt, not polished performance reports.