Undiscovered Territory

7-40 Challenge | Round 4, Day 29


I’ve been calling promoting my creative work a foreign country. A place I don’t speak the language, don’t know the customs, don’t belong. I’ve been treating it like something that requires a translator or a guide just to survive.

That’s the wrong metaphor. And the wrong metaphor was keeping me stuck.


A foreign country means I don’t belong there. The terrain is hostile, the language is incomprehensible, and I need someone else to navigate for me. That framing makes me a tourist — passive, dependent, out of my depth.

Undiscovered territory means the map hasn’t been drawn yet. I have skills that transfer. I’ve navigated unmapped ground before. The terrain isn’t hostile — it’s just unfamiliar. And the only way to map it is to walk it.


Lewis and Clark had a mission before they had a map. They knew the destination — the Pacific. They didn’t know the terrain between here and there. They walked it anyway, and the map got drawn behind them.

I know my Pacific. It’s not a revenue number. It’s freedom. It’s influence. It’s the ability to create things that matter to people, that uplift and inspire them, and also provide me the means to accomplish the goals that I have.

Everything between here and there is not a foreign country — it’s just unmapped territory. And no one else is going to map it for me, because no one else has my combination of skills, products, and goals.

The good news is I believe I’m right where God has me, and that I’m walking with Him through this uncharted territory. It’s exciting. It’s scary. But it’s time to find that Pacific shore.

Data Is Communication

7-40 Challenge | Round 4, Day 26


I had a conversation today that connected twenty years of my career to the thing everyone’s trying to figure out right now.

I work in data management. I’ve spent two decades as the person who sits between business teams and technical teams, translating what one side needs into language the other side understands. Business people don’t think in tables and queries. Technical people don’t think in revenue targets and customer experience. Somebody has to build the bridge. That’s been my job.

Today I realized that’s exactly what people need to learn to do with AI.


I learned this firsthand when I asked AI to edit my novel. I said “edit this” and got hallucinated rewrites. I said “read this, tell me what’s wrong, don’t touch anything” and got a sharp, tireless reader. Same tool. Same book. The only difference was how clearly I defined what I needed.

That’s not a technology problem. That’s a communication problem. And it’s the same communication problem I solve at my day job every single day.

The people getting great results aren’t smarter. They’re clearer. They define the problem before they ask for a solution. They tell the AI what they know, what they don’t know, and what good looks like. They argue when the output doesn’t match their intent.

They’re doing data architecture for their own thinking — organizing what they know so someone else can work with it. They just don’t know that’s what it’s called.


For twenty years I’ve been building the bridge between people who have information and people who need to use it. The tools on both sides changed today — one side is a person, the other side is a machine. But the problem is identical: get the meaning across, not just the words.

Data is communication. It always was. AI just made it urgent for everyone to learn how to say what they mean.

The Joining Tables Moment

7-40 Challenge | Round 4, Day 25


My freshman year of college, I convinced myself I couldn’t handle music theory. I had the brain for it. I just didn’t believe I did. So I enrolled in fundamentals instead — the kiddie pool — while my entire cohort moved ahead into the real coursework.

I never caught up. That one decision put me out of step with the people I was supposed to be learning alongside, and I eventually changed majors. Not because I lacked the ability. Because I chose the safe version and paid for it with a path I never fully chose to walk.


Years later, I was working a data job and feeling my way into being an analyst. I’d pull data out of our system, export it to Excel, and got crazy good at making spreadsheets do what I needed. I didn’t know there was a structured query language that could do everything I was doing — faster, better, and repeatable.

I was really good at Excel. And I was really scared of SQL.

Then one day, someone showed me how to join tables. How to connect two data sets with a single statement and pull exactly what I needed. A light went off. I looked at it and thought: get out of my way.

Not only did I understand what I was looking at — it supercharged my thinking about it. Everything I’d been doing by hand, I could now write in scripts that ran themselves. I went from scared to unstoppable in one afternoon. And I never went back.


Same person. Same pattern. Two different choices, two completely different outcomes.

Right now I’m standing at the edge of another piece of unmapped terrain — getting the things I’ve built in front of people. Promotion. Marketing. Asking strangers to care about what I’ve made. I haven’t walked it yet, and the absence of a map feels like proof that I can’t do it.

But that’s what SQL felt like too. And I know what it cost me the time I chose the kiddie pool instead.

Somewhere in the first few steps, there’s a join tables moment waiting. I just have to start walking to find it.

I Told the AI to Edit My Book

7-40 Challenge | Round 4, Day 23


Earlier this year, I finished my first novel — 105,000 words of a YA superhero story set in the 1990s. It needed editing. I had Claude. I figured this would be straightforward.

I said, essentially: let’s edit this.

The AI started rewriting my story. Not editing — recreating. It changed plot points. It rearranged material. It put scenes out of order and stopped tracking what had happened in previous chapters. It was hallucinating its way through my manuscript, and the output was getting further from my story with every pass.

So I stopped and changed how I talked to it.


Instead of “edit this,” I said: read this chapter. Read the chapters before it. Tell me what works and what doesn’t. Point out the parts that are heavy, the parts that don’t explain enough, the parts that slow down. Do not make any edits. Just show me the problems.

And it worked.

The AI became a sharp, tireless reader who could point out structural issues I was too close to see. I made the decisions about what to change. I did the rewriting. But I had a partner who could read my 105,000 words without fatigue and tell me where the story was dragging, where a character’s arc was inconsistent, where I was telling the reader something the scene had already shown.

That manuscript lost nearly half its weight through editing. Every cut made it better. And the AI didn’t make a single one of those cuts — I did.


The difference between the first attempt and the second was entirely in how I defined the problem. “Edit this” is not a problem statement. It’s a wish. “Read this and tell me what’s wrong without touching it” is a problem statement with boundaries, criteria, and a clear role for each party.

The AI didn’t get smarter between attempt one and attempt two. I got clearer.

The Wing-It Tax

7-40 Challenge | Round 4, Day 17

I was 19 and a bit unobservant. I signed up for what I thought was personal finance. I wanted to learn how to balance my checkbook. I ended up in fundamentals of business finance, learning bond valuation.

I did what I always did in college — I winged it. Showed up, skated through, and crammed at the end. Pretty sure I got a D. I was happy with it.

In retrospect, I’ve worked a corporate job for almost twenty years. The financials aren’t that hard to understand. If I had taken some focused time early that semester, I would have learned the material and been fine. It wasn’t a smarts thing. It was a wing-it thing that almost bit me.

I leaned on talent for most of my life. Smart kid, underachieving student. A 2.87 GPA in my undergrad, mostly propped up by passing all of my music courses.

Then I went back for my master’s degree and decided to get my act together. I studied. I did the assignments. I prepared instead of crammed. I graduated with a 3.95.

The only thing that changed was the work ethic.

I think most people romanticize the idea of working well under pressure. I think that’s nonsense. Very few of us actually work well under pressure we manufactured through our own laziness. We just convince ourselves we do because we survived it. Surviving isn’t thriving. And the work that comes out of a last-minute scramble shows it.

If I could go back and tell the kid in that finance class one thing, it would be this: the difference between a 2.87 and a 3.95 wasn’t talent. It was deciding to stop paying the wing-it tax.