Every week, a team somewhere shows off an AI demo that gets a standing ovation in the boardroom and quietly dies three months after launch. Not because the idea was wrong. Because the architecture wasn't built for the real world. Here are the six mistakes we see repeatedly — and what to do instead.
1. The demo runs on your laptop. Production doesn't.
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2. You're using an API. You should own the pipeline.
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3. Your retrieval layer isn't production-grade.
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4. You have no monitoring on the model layer.
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5. Cost was an afterthought, not a constraint.
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6. You deployed once and haven't touched it since.
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