Brian

If you focus on the current tools and patterns, you stay effective, but your knowledge can expire quickly and you end up rebuilding your playbook every quarter.

If you focus mainly on durable fundamentals, you build long-term leverage, but you risk falling behind on the practice methods that deliver results right now.

How do you choose what to learn, teach, and operationalize when the payoff window for tool-specific mastery keeps shrinking, but ignoring the tools also carries a real performance penalty?

So that's what you're going to hear the two co-hosts dive into, the two AI co-hosts, I should say, in case you've never listened to these before.

And also what's a little different is that they are talking about very recent events as they get going in here, and I find that interesting.

Now that's probably because of the data they had to build the

you know, podcast off of.

So there's not, it's not like there's been some huge impact or improvement in how notebook LN works, but it's still interesting to hear these two AI co-hosts and the way it's sort of set up.

Um, talk well, like humans that are going through this very, very interesting in itself is its own.

There's probably a couple of conundrums there about these conundrum episodes, very meta of me.

Maybe I'll do that someday, but for now, I hope you enjoy this episode.

It's about education.

It's about AI literacy.

It's about AI.

These are all the things that I care about deeply.

So this one's right up my alley and I really enjoy it.

Hope you do too.

Have a wonderful Saturday.

She goes to give me knuckles, and I'm like...

Ginny.