Six AI Product Principles No One Tells You—And How I’m Applying Them in My Build

Source: Nate’s Newsletter Date: 2025-05-13 URL: https://natesnewsletter.substack.com/p/six-ai-product-principles-no-one

Summary

With 75% of AI product launches failing to meet their goals, Nate distills six principles from failure analysis (using Klarna’s high-profile AI deployment as the cautionary case) and demonstrates them through PromptKit — his own product for treating prompts as first-class citizens with systematic testing and quality assurance. The dogfooding structure gives the principles credibility beyond theory.

Implications

Agent-product positioning thread. The absence of robust prompt testing and evaluation tooling as a gap in AI infrastructure — identified in May 2025 — has since seen some movement, but remains underdeveloped relative to other parts of the stack. PromptKit as a product signals a market: teams building AI products need prompt management systems, not just prompt guides.

Enterprise adoption thread. The 75% failure rate is the central enterprise AI story: most investment isn’t delivering. Klarna’s case is instructive because it was a high-visibility, high-confidence deployment that produced visible failure — the kind of example that shapes board-level risk appetite for AI projects.

Watch: Whether the prompt testing / evaluation tooling category consolidates around a few products or remains fragmented — and whether Anthropic or OpenAI builds this capability natively into their platforms, eliminating the independent tooling market.