Most of us are using AI the same way:

Ask a question.

Get a great answer.

Maybe go a little deeper…

And in the moment, it feels incredibly productive.

Clear. Insightful. Like you’ve really learned something.

And then a few hours later… it’s gone.

Why does this happen?

In this Lab Notes episode, I break down the brain science behind why learning with AI often doesn’t stick, even when it feels like it should.

There are a few key mechanisms at play, including cognitive offloading (outsourcing the work of thinking), the difference between recognizing and generating information, and the lack of “desirable difficulty” that our brains actually need to learn. We also explore the fluency illusion - why something can feel clear in the moment without being deeply understood - and how instant answers may be disrupting dopamine-driven learning.

AI isn’t the problem. But the way we’re using it may be eroding how we learn. Over time, that creates a gap between what feels like progress… and what we can actually use in our day-to-day lives.

In this episode, I also share two simple ways to learn with AI instead of just consuming it:

• Think First, AI Second

• The No-Look Test

The goal isn’t to use AI less, it’s to use it in a way that actually builds your brain.

Timestamps

00:00 – Why AI learning doesn’t stick

00:45 – The illusion of learning with AI

02:28 – Cognitive offloading (why you don’t remember)

04:00 – Recognition vs generation

06:20 – Why easy learning doesn’t last

07:10 – Handwriting & deeper encoding

08:40 – The fluency illusion

09:30 – Why instant answers hurt learning

11:50 – Think First, AI Second

13:00 – The No-Look Test

14:30 – The real goal: learning that sticks