Slip Sliding with a Cannonball

Launching AI apps for education right now feels like trying to walk across a parking lot covered in black ice.

Not the dramatic kind where everyone sees it coming. The sneaky kind. You step out with confidence, “I know what people need,” and the universe responds by gently removing friction from reality. Suddenly you’re doing accidental figure skating in front of your own assumptions.

That’s the landscape. It’s changing fast, it’s slippery, and it punishes certainty.

And yet this is exactly why it’s such a good moment to build.

Because the real problem hasn’t changed: studying is hard in the most irritating way. It’s not “climb a mountain” hard. It’s “push a shopping cart with one broken wheel” hard. People work, they try, they care, and too often the results don’t match the effort. They read, they highlight, they re-read, they feel busy, and then they sit down for the test, or the certification, or the GED, or the onboarding assessment and realize their brain has replaced half the material with elevator music.

So here’s the bet we’re making: the next wave of education isn’t going to be defined by bigger content libraries. It’s going to be defined by better practice, better feedback, better pacing, better clarity about what matters, and better ways to turn “I saw it once” into “I can actually use it.”

That’s why we’re launching a set of AI-powered education apps that aren’t trying to be flashy. They’re trying to be useful. And yes, we’re aiming at the messy middle: real learners, real teachers,

real constraints, real life.

First: our Study application.

It’s built for the people who have every reason to learn and not enough time, energy, or structure to make studying reliably work. GED students. Adult learners. People in corporate training who suddenly need to learn a new set of terms, procedures, concepts, and vocabulary fast. Students in STEM classes trying to keep chemistry from eating them alive. Study groups where half the battle is figuring out what to study and how to study it.

The whole idea is simple: studying shouldn’t feel like wandering around a dark house looking for the light switch. It should feel like a guided sequence of practice that adapts to you.

When it works, it does three things.

It helps you figure out what matters. Not what’s interesting. Not what’s long. What’s testable, foundational, and connected to other ideas.

It helps you practice retrieval. That’s the secret sauce most people never get taught: learning isn’t “taking information in,” it’s “pulling it back out.” If you can retrieve it, you own it. If you can’t retrieve it, you don’t. AI can generate infinite pages of notes, but the win is creating the right kind of practice: questions that expose gaps, prompts that force explanation, examples that test understanding, quick checks that show whether you’re actually improving.

And it helps you keep going. Because motivation isn’t a personality trait. It’s a system. When learners can see progress and see exactly what to do next, studying stops feeling like self-punishment and starts feeling like momentum.

Now, the obvious question: can this work outside GED and STEM? What about literature, sociology, psychology, history?

Yes. And here’s why I’m confident: those subjects have “vocabulary,” too, just a different kind.

In literature, you’re learning how to notice patterns, interpret themes, connect evidence to claims, understand character motivation, analyze passages, and explain meaning clearly. In sociology and psychology, you’re learning frameworks, theories, variables, mechanisms, and how to apply concepts to real situations without turning everything into mush. In history, you’re learning causality, context, chronology, and interpretation. In all of them, the mistake is the same: learners confuse familiarity with mastery.

A good Study app doesn’t care what the subject is. It cares about the shape of learning: explanation, application, retrieval, feedback, repetition, and increasing complexity. That works everywhere humans learn things, which, last I checked, is still most places.

Second: yourclassroom.ai, the teacher-sharing app.

This one is personal.

Teachers already have brilliant AI workflows. They’re trying them in the halls of K–12 schools. They’re swapping ideas in faculty lounges. They’re texting each other screenshots of prompts and rubrics and “try this tomorrow” hacks. They’re inventing creative, clever, classroom-tested uses of AI, and almost none of that value is being captured, shared properly, or rewarded.

So we’re building a place where teachers can share what actually works and get paid for it.

Not theoretical “best practices.” Not admin-mandated initiatives. Not “I read a thread about this once.” I mean teacher-made resources built out of real classroom life: prompt templates, lesson structures, role-play simulations, differentiation strategies, feedback workflows, literacy supports, project scaffolds, assessment alternatives that reduce cheating by design, and smart ways to use AI without sacrificing human connection.

Educators shouldn’t be the unpaid research and development department for edtech companies. If you build something that helps other teachers teach better and helps students learn more deeply, you deserve more than a pat on the head and a “nice job.”

This is us saying: creators and colleagues, brothers and sisters, what’s up with that? Let’s fix it. Let’s build a teacher-to-teacher economy where proven ideas travel fast and the people who created them aren’t invisible.

And yes, we mean globally.

Nigeria, Rwanda, Colombia, we want you in this story, too. We do not believe world-class learning support should be restricted to wealthy zip codes or elite institutions. If educators have creativity and students have desire, then the tools should be accessible. The future of education is not “some countries get AI and others get left behind.” The future is everyone gets better tools, and we build the culture to use them well.

Third: our skill-and-knowledge tracking app, currently called TransformLearning, because it doesn’t have a cute name like Peekaboo or Bondy yet.

This one is the weirdest in the best way.

It’s built on a simple insight: people study harder when they can see where they are.

There’s a psychology concept called the Hawthorne effect, the idea that when people know they’re being observed or measured, behavior changes. Often performance improves, at least in the short term. I’m not using this as a gimmick. I’m using it as a design principle: visibility changes effort. Clarity changes effort. Feedback changes effort.

So imagine a student who doesn’t just have grades. They have a map.

A map of what skills and knowledge they’re supposed to be developing in a course, major, or training program. A map of what they’ve practiced, what they’ve demonstrated, what’s shaky, what’s solid, what’s improving, and what’s been ignored, not out of laziness, out of confusion.

Now make it smarter: it reads the syllabus and course materials. It extracts the explicit learning goals, sure, but it also tries to identify the implicit ones.

Because here’s a truth that makes both teachers and students nod grimly: sometimes the real curriculum is invisible.

I used to teach implicit learning, skills people acquire without being directly taught. And AI helped me see how much of education lives in that category. Time management. Planning. “How to be a student.” How to break down tasks. How to interpret instructions. How to communicate professionally. How to navigate basic marketplace logic. The hidden prerequisites that decide whether someone succeeds.

TransformLearning aims to make the invisible visible. Not to shame students. To empower them. To say, “Here’s what’s actually going on. Here’s what you’ve built. Here’s what you need next. Here’s how to move.”

So that’s the cannonball we’re trying to catch.

A Study app that makes practice effective, not miserable.A teacher-sharing marketplace that treats educators like creators, not content-consuming employees.A skills-and-knowledge map that helps learners understand where they are, especially in the hidden parts of learning that most schools never name.

Now we need the people who always show up early to the future.

The early adopters. The educators with a little rebel-engineer DNA. The ones who experiment, iterate, and share. The creators who don’t just get excited, they follow through. The teachers who know the best ideas don’t come from corporate memos. They come from classrooms.

The ground is slick. The landscape is shifting. The certainty is fake.

But the opportunity is real.

Let’s catch the cannonball.