A data scientist at Gramener built 86 AI applications in one year, averaging one app every 4.2 days. After a forensic audit of 25,000+ lines of code, they discovered their technical debt was 40-55%, significantly lower than the industry average of 60-80%. The audit revealed an LLM-first architecture pattern that reduced development time by 75%.

However, the analysis also exposed critical issues: one real XSS vulnerability via unsafeHTML and ~500 lines of duplicated code. Surprisingly, two of three initially flagged 'critical' vulnerabilities were false alarms after proper threat modeling. This case study proves that velocity and quality aren't mutually exclusive, provided you make deliberate architectural trade-offs and implement proper security sanitization.