AI Features Need Product Edges, Not Just Better Prompts

Short summary

AI features often fail not because models are poor, but because surrounding product infrastructure is treated as an afterthought. The author shares concrete examples from an iOS fitness app using Claude: credit management, offline handling, auth tokens, and error mapping. Shipping production AI requires solid software engineering around a probabilistic dependency—tests, edge cases, and consistency matter more than prompt quality.

• •AI features fail due to poor product infrastructure, not model weakness
• •Real product quality comes from credit systems, offline handling, auth, and error mapping
• •Shipping AI requires rigorous testing and edge-case handling, not just better prompts

Generated with AI, which can make mistakes.