Hey all,

It's an oddly cool day in Austin today. This entire weekend has felt like a real Spring. Taking in the moments before the 100 degree marathon begins.

Today has guest posts from Jenna and Patrick. Big thanks to them! I also go on tangent with my latest favorite word: fascination.

With that, let’s dive into it.

What's Top of Mind

1) The struggle is the learning

By: Jenna Castaldo

I often think about the tweet that Adam surfaced from Mark Cuban about those who use AI to learn everything, and those that use it so they don’t have to learn anything.

I’m a big proponent of using AI for creating efficiencies and automations where my brain could be working on more impactful & fulfilling tasks, and using it as a thought partner, too.

But using it so that you don’t have to learn anything has naturally rubbed me the wrong way, especially in my role.

Here’s why:

Think about a sport you’re familiar with in theory but never actually played. Let’s take professional football (the one w/ hands) for example (and Go Birds). I could read all day about how to play the game, how the plays are ran, etc. I’ve watched tons of games, and I could verbally recite how the game is played. But if I stepped foot on a professional football field for the first time, I think I would actually die. (Maybe not die, but I surely would not get drafted for any round pick).

However, me actually stepping on that field is a better step in me performing the game than all the info I could read. (Pause, read that again.)

What’s happening in that scenario is what happens when we lean on AI to learn something new. Our brains naturally use what are called desirable difficulties (the productive friction of confusion, recall attempt, and error correction) to build lasting knowledge and create pathways that lend itself to pattern recognition over time.

Essentially, experiencing struggle in learning is a good thing. Using AI to learn eliminates that struggle by design.

Which brings me to one of the things I think about most in my role - how do we make sure that we create coaching & training experiences for our rev team that enables them to be those first round picks for the sales field?

We action on this often - leveraging socratic questioning frameworks, implementing live quizzes in our new onboarding, live pitch practices and role plays, teach-back methods, and so on. These methods could be frustrating for those on the other end at first, and even time-consuming, but they are what build the pathways that allow them to thrive in the field.

A mentor once told me the most important thing you'll do in your career is build skills - they compound over time, and no one can take them from you. What’s waiting on the other side of the learning struggle is a lifelong surplus of skills, so leaning into the struggle, even if it may not fit the “efficiency” bill, truly fulfills that.

I'm curious - what's one thing you've been outsourcing to AI, that you should probably be struggling through learning yourself? Feel free to slack it to me this week and we can chat through it! 

2) Talk to Claude

By: Patrick Branigan

Our resident client success management badass Jeff K. approached me this week asking if I could help him use Claude. "I want to give my brain to my team so they're better equipped to handle certain situations," Jeff said. He wanted to know more about projects, skills, chats, hooks, etc. So we did a brief 101 on the native app. When all was said and done I simply said to Jeff, "Talk to Claude as if it were one of your juniors and see where it leads."

I left my conversation with Jeff slightly concerned that I hadn't given him a true answer. So I turned to Claude.
It's really easy to default to: input your problem, AI outputs your solution. The illusion of convenience, speed, and accuracy is spellbinding – I get it! However, what I keep noticing in my own use of AI (especially with Claude Code) is that some of its highest value output happens well before I arrive at any answers.

I took the transcript of our conversation and fed it to Claude, and I thought out loud as we conversed about the topic at hand. What we eventually arrived at wasn't an explanation or an answer for Jeff. It was clarity for me about what he actually needed.

Jeff simply needed something concrete to try.

I had Claude Slack Jeff our conclusion:
--

Hey Jeff — was thinking more about your "projects vs skills vs customization" tangle. I think the unlock is just realizing they're all about where context lives. Quick mental model:

• Chat — nothing persists. Throwaway stuff.

• Customization — about you, applies everywhere. Role, tone, how you like answers.

• Project — a workspace with its own files + instructions. A place you go to work on something.

• Skill — a packaged workflow Claude pulls up when the task matches. A thing Claude knows how to do.

When you're stuck picking: is this a place I work, or a thing I do? Place → Project. Thing → Skill.
Two moves I'd start with:

1. One Project for the creator program — drop in tone guide, recent posts, team roster. Every creator chat starts pre-briefed.

2. One Skill for the Tuesday reminder — once it's a skill, we can wire it to a schedule + Slack so it just runs.

Build those two, live with them a couple weeks, then let's hop on another call again. If you have questions just hit me up. For our next call bring me:

• 5 real before/after examples of the positive-vs-negative client framing thing

• Where the "previous week's posts" data you mentioned actually lives (Drive? Hex? somewhere else?)

• One weekly workflow you wish you didn't have to do

That'll turn our next call into building something, not just theorizing. Grab whatever time works on my calendar — no rush, drop it whenever you're ready.

--
The message doesn't solve his problem. It sets up our next conversation to be about real artifacts instead of abstract concepts. It frames the challenge at hand. It contextualizes it. And if you're paying enough attention, you'll notice it's also teeing up a fruitful opportunity for two human beings to connect and problem solve together (with an AI transcribing everything, of course!)

The more you give AI, the better the chance you have at it accurately serving you conveniently, expeditiously, and accurately.
AI might feel instantaneous. But take time with it. Ask questions. Ask for clarity. Ask to be taught. Tell it it's wrong. Tell it why you believe you're right. Have it prove to you its value, and deliver back to it the value you hold.

At the very least, talk to it as if it were one of your juniors and see where it leads.

3) Find what fascinates you

Fascination is the most underrated driver of success.

Not talent. Not discipline. Not even work ethic.

Fascination.

Here’s what I’ve noticed about people operating at the highest level: the area where they’re having the most success is almost always the area they’re most fascinated by.

It might be people. It might be process. It might be product. It might be technology. But there’s something pulling them deeper than everyone else.

Anyone can get to a surface-level understanding of how something works. The real question is what happens next. Do you stop once you “get it”? Or do you keep going?

Fascination is what pulls you past the basics into tinkering. It’s where curiosity and passion collide, and then compound over time. It creates consistency without forcing discipline. You’re not white-knuckling the work. You’re chasing it.

I see it in my own life. There are things I don’t casually follow. I go deep. Not because I have to. Because I can’t help it.

You won’t be fascinated by everything you work on. You probably won’t be fascinated by most of it. That’s normal. But if you can find the part that pulls you in, the rest gets easier.

That’s why, when we interview people, I don’t want comp or benefits to be the reason they say yes. Those things matter, but they don’t create exceptional performance. What I’m listening for is simpler:

What are you fascinated by here?

When someone answers that honestly, everything changes. Their curiosity takes over. Their effort becomes natural. Their ceiling gets higher.

You can see this playing out with AI right now. The gap between people isn’t ability. It’s interest. The ones leaning in aren’t necessarily more talented. They’re more fascinated. They’re exploring, experimenting, and compounding faster than everyone else. Six months from now, that compounding will look like a chasm.

So here’s the challenge: if you’re fascinated by something, especially AI, don’t keep it to yourself. Teach it. Share it. Bring people along.

That’s how fascination scales. That’s how individuals turn into teams that learn faster than everyone else. And that’s how you build something that compounds.

QUESTION OF THE WEEK

What's a fascination you've had most recently?

Thanks for giving it a read. Make it a great one.

Adam