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Why did Cursor see great adoption, but your AI product is not finding any takers?
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Why do some AI products take off, while others flop?
And no, it’s not about better models, it’s something deeper
The real predictor is – CAIR = Confidence in AI Results
High CAIR = high adoption.
Low CAIR = users won’t even try your feature, no matter how advanced your model is.
In case of code assistance tools like Cursor
Risk: Low – If you don’t like the suggestion, delete ot tweak it.
Value: High, Saves hours of effort
Now imagine if Cursor auto-pushed code to production.
Same AI model, but now Risk = High.
CAIR crashes. Adoption dies.
Here are 3 ways to boost CAIR (and adoption):
1. Human-in-the-loop at the right moments
2. Reversibility – make it easy to undo
3. Explainability – show why AI did something
So, before asking “Is our model good enough?”, ask:
“Is our CAIR high enough for adoption?”
Your biggest product wins are not in better models, but in better trust design.
You don’t need “perfect” AI. You need confident users!
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Happy learning!
If you have any queries or suggestions, share them with me on LinkedIn – https://www.linkedin.com/in/nikhileshtayal/
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