11 weeks of iteration.

And the data team was killing it.

We’d just built the startup’s first AI model.

Everything was going right.

Tight process.
Deep insights.
Solid model performance.


When I presented to the executive team,

I talked about model performance and customer impact.

Then I added… “By the way, this model uses Deep Learning.”

I was trying to sound impressive.

In reality, I was perpetuating a myth.


The myth is that “more advanced” equals “more value.”

“Our model doesn’t just use machine learning — it uses deep learning.”

That’s obviously better. Right?


Our job is to “delight users in hard-to-copy, margin-enhancing ways.”

I love how Gibson Biddle describes the job of product teams.


Using advanced techniques like Deep Learning MAY help us ‘delight users’ and make the product ‘harder to copy’.

But if a simpler technique works just fine, then we’re just hurting our margins.

We’re spending precious R&D budget on cachet, not customer value.

So, ignore the terms.

Keep it simple. Solve the problem. Serve the customer.

That’s what matters.

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