common-pitfalls-when-building-generative-ai-applications

Common pitfalls when building generative AI applications

Article: https://huyenchip.com/2025/01/16/ai-engineering-pitfalls.html

In short, here are the common AI engineering pitfalls:

  1. Use generative AI when you don’t need generative AI
    Gen AI isn’t a one-size-fits-all solution to all problems. Many problems don’t even need AI.

  2. Confuse ‘bad product’ with ‘bad AI’
    For many AI product, AI is the easy part, product is the hard part.

  3. Start too complex
    While fancy new frameworks and finetuning can be useful for many projects, they shouldn’t be your first course of action.

  4. Over-index on early success
    Initial success can be misleading. Going from demo-ready to production-ready can take much longer than getting to the first demo.

  5. Forgo human evaluation
    AI judges should be validated and correlated with systematic human evaluation.

  6. Crowdsource use cases
    Have a big-picture strategy to maximize return on investment.