Addison W. Brown

The ECON 384 syllabus went up in August. I fed the readings to Kachieve and got five lessons back — 619 questions, written from the same chapters the class gets tested on.

Generating questions is the easy half. The half I care about is the button sitting under every one of them: Teach me. Press it when you’re stuck and the app doesn’t explain the answer at you. It writes a ladder.

It takes the question you missed and generates a run of easier ones leading back to it, each feeding the next. The first is a layup. The last is the question that stopped you, word for word. Nobody hands you the answer — you get walked to the point where you can produce it yourself.

A month after Conjugo — the Spanish app in the next chapter — Katie and I were building again. Kachieve is the app in the chapter above; this one is about what building it cost, and what it bought.

Upload your notes and they become practice problems that keep quizzing you until you actually know the material. Everything else — the ladders, the recursion, the class links — grew out of that one loop.

The concept is mine, and so is every line of code — I came up with it, prototyped it, and built it myself, putting more than a hundred million tokens through Claude Code across Kachieve and the side projects orbiting it. Learning AI was the point. Somewhere along those hundred million tokens, I got good.

In March 2026, between accounting problem sets and Spanish homework, I built Conjugo — a language app with one conviction at its core: technology should put two people face to face, not stand between them.

It had the serious machinery — spaced repetition on the same algorithm as Anki, AI‑written sentence cards read aloud in a synthesized native voice, a knowledge map covering all eighteen lessons of the Wake Tech Spanish curriculum. But the part I loved was the battles: head‑to‑head flashcard races over live video, and a matchmaking mode that paired you with a native Spanish speaker learning English. You teach yours, they teach theirs. Both people walk away better.

It started as a little script that stuffed AI‑generated sentences into my own Anki deck. Eleven days and eighty‑seven commits later, it was a real product at yoconjugo.com, with a team of four — my girlfriend Katie designed it, and two friends, Reece and Amos, ran marketing and translation. I wrote all of the code.

College and I got off to a slow start. One summer term at nineteen, a C in precalculus — and then two years of not going back.

What pulled me back wasn’t a deadline. It was a sentence. Warren Buffett calls accounting the language of business — and I was running a business every day: pricing hours, flipping machines, watching money move. So in the fall of 2024 I re‑enrolled at Wake Tech for exactly one class, Principles of Financial Accounting.

I started the way most people start: with the biggest truck I could justify and the most expensive equipment on the lot. It looked like a business. It felt like a business. It was also the least profitable version of the business I would ever run.

So I changed what I measured. Not revenue — profit per hour worked. Every decision after that came back to the same number: which machines to keep, which clients to let go, how to route a day so the truck spent less time on the road and more time earning.

It started with a question I couldn’t put down: why does one video pull ten million views while a nearly identical one pulls ten thousand?

I went looking for patterns — thumbnails, titles, the first ten seconds, the promise a video makes and whether it keeps it — and I kept score in a spreadsheet. The spreadsheet, if I’m honest, sucked. The tools to build what I could see in my head didn’t exist yet. But the thinking underneath it held up, and it rewired how I watched everything.

The first thing I ever studied on my own — nobody assigning it, nobody checking — was the stock market. I finished high school and fell into it completely.

The plan, and at nineteen it felt entirely reasonable, was a quantitative trading firm. So I read — dozens of books, one after another: the value investors, the macro traders, the market histories. The one that rewired me was Ray Dalio’s. He treats the world as a machine — the same causes producing the same effects, over and over, for anyone patient enough to map them. I believed him. I still do.

So I acted on it the only way I knew how: I taught myself just enough code to program a trading algorithm. That sentence is most of the triumph of this chapter. The firm never followed. Between my ideas and my abilities sat everything I hadn’t learned yet — real programming, real statistics, the slow fundamentals — and no amount of conviction could stand in for them.