Building AI Agents Part 1: Defining Purpose, Designing Prompts, and Selecting Models
Towards AI
•
Machine Learning
Generative AI
The critical first steps that determine whether your AI agent succeeds or fails in production - with real examples from banking, retail, and healthcare A healthcare startup spent six months building an AI agent for patient triage. They used the latest GPT-4 model. They hired experienced ML engineers. They built a beautiful interface. The impressed investors. Then they launched to real clinics. Within days, nurses stopped using it. The agent asked irrelevant questions. It missed critical symptoms. It provided inconsistent advice.