Case Studies: When AI Goes Wrong
Three critical production failures that taught us everything about building reliable AI systems. Each case study shows the problem, diagnosis, solution, and lessons learned.
RAG Failures
Retrieval and context issues that lead to dangerous answers
Temporal & Data Issues
Outdated information and version control problems
Agent Reliability
Tool validation and agent behavior failures
Why These Failures Matter
These aren't theoretical examples—they're real production failures that caused business impact, user confusion, and system downtime. Each case study includes actual Langfuse traces, before/after metrics, and production-ready code solutions.
The Problem
A user asked, 'Can I expense a new coffee machine for my home office?' The retriever fetched a permissive policy document but completely missed the exclusions list that explicitly forbids kitchen appliances.
Impact:
Partially correct but subtly wrong answers are more dangerous than obviously wrong ones. This could have led to policy violations and financial disputes.
Key Metrics
Key Lessons
- Faithfulness alone is insufficient - high faithfulness with wrong context is dangerous
- Contextual Recall is critical for policy and compliance use cases
- +2 more lessons...
The Problem
Users consistently received answers based on outdated PTO policies. The current policy existed in the knowledge base but was buried in a different section with poor metadata.
Impact:
Employee confusion, HR disputes, and potential legal compliance issues. Trust in the AI system eroded rapidly.
Key Metrics
Key Lessons
- Temporal metadata is essential for any time-sensitive information
- Hard filters prevent outdated content from reaching users
- +2 more lessons...
The Problem
Production agents were calling non-existent tools or using malformed parameters, causing system crashes and complete task failures.
Impact:
System downtime, failed user tasks, and complete loss of trust in the agent system. Emergency rollback required.
Key Metrics
Key Lessons
- Tool validation is non-negotiable for production agent systems
- Circuit breakers prevent cascading failures from tool errors
- +2 more lessons...