DJC Insights
A Failed AI Deployment and the Lessons Learned
We talk a lot about success. But we learn more from failure. This is the story of Project "Hydra"—a failure we orchestrated in 2024.
Industry: Logistics Goal: Automate Customer Service for "Where is my package?" queries.
The Mistake: Over-Confidence in "Magic"
The client wanted a chatbot that could "handle everything." "Just give it the policy documents and let it answer," they said. "Sure," we said. (Lesson 1: Never say sure to this).
We fed the AI 50 PDFs of shipping policies, customs regulations, and insurance details. We connected it to the live tracking database. We launched it to 10,000 users.
The Crash
Day 1 was a disaster.
Issue 1: Hallucination A customer asked: "Can I ship a lithium battery to Fiji?" The AI found a document about shipping batteries (allowed) and a document about Fiji (allowed). It said "Yes." Reality: The carrier specifically banned lithium to islands proper due to air freight rules buried in a footnote. Result: Package seized at customs. Client furious.
Issue 2: The Loop The AI was too polite. Customer: "Where is my package?" AI: "It is in transit." Customer: "But it's been 5 weeks." AI: "I understand. It is in transit." The AI had no ability to escalate to a human because we hadn't built an "Escalation Trigger."
The Turnaround
We shut it down after 48 hours. We rebuilt it with Guardrails.
- Scope Reduction: The AI was banned from answering regulatory questions. It simply said "I will connect you to a specialist for dangerous goods."
- Hard Logic: For tracking, we stopped using LLMs. we used code. If date > 30 days, outcome = "Lost". No AI interpretation allowed.
The Lesson
AI is not a lawyer. It is not an expert. It is a text predictor. If you need 100% accuracy on legal/compliance matters, do not use generative AI. Use a lookup table.
We failed because we used a creative tool for a logical problem.