Demo Is Not the Product

Short summary

Demo success doesn't guarantee production success—the architecture that impresses stakeholders often doesn't survive real-world constraints. Production AI systems fail on four fronts: manual evaluation doesn't scale, prompts break on unexpected inputs, token costs explode, and model upgrades require rewrites. Design evaluation and cost monitoring upfront, separate model logic from code, and build abstractions for model swapping to avoid costly six-month rewrites.

• •Demos work; production AI systems fail on evaluation, prompts, costs, and model constraints
• •Design evaluation infrastructure, cost monitoring, and model abstraction from the start
• •This prevents costly rewrites and accelerates shipping

Generated with AI, which can make mistakes.