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Why AI projects can fail

    1. Solve the wrong problem

    2. Automate a system that is better handled manually: customer support

    3. Buy too many tools

    4. Not keeping track of when you are paying per request or not

    5. Not using tool aggregators

    For example Cursor lets you use a half a dozen of the latest models essentially unlimited for $20 per month

    6. Not caching results

    7. Too much feature creep

    8. Vibe coding train wreck

    9. Not utilizing a human in the middle system architect

    10. Too few point of human in the middle checkpoints

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