Edition 368 | August 31, 2026

The Dyslexic AI Newsletter by LM Lab AI

Reading Time: 9 minutes | Listening Time: 11 minutes

In 1685, a man named Thomas Budd wrote about education as a tool for building a thriving society. Not education as information delivery. Education woven together with community, work, character, and citizenship, a practical contribution a person could actually make once they were done learning.

He was not writing in a world anything like ours. But the underlying question he was asking is close to identical to the one this entire series has been circling.

What is education actually for, given the world we're actually in right now?

Every few centuries, the honest answer to that question changes, because the conditions underneath it change. I think we are living through one of those shifts right now, and I want to spend this edition laying out what I think the answer looks like.

Before I describe what I think needs to change, I want to give credit to what worked, because it did work, for a long time, for good reasons.

Traditional colleges became successful institutions because they solved several real problems at once. Knowledge was scarce, and colleges centralized the people who held it. Expertise was hard to access anywhere else, so gathering it in one place created enormous value. A degree became a trustworthy signal of competence, because completing the process actually meant something. Being physically present with other learners built networks and relationships that mattered for decades afterward. And the whole structure prepared people for careers that stayed relatively stable across an entire working life.

For hundreds of years, none of that was broken. It was genuinely well designed for the world it existed in.

The issue is not that colleges failed. The issue is that the world underneath them changed, and the assumptions never caught up.

Knowledge used to be scarce. It is abundant now. Information used to be difficult to access. It is instantly available now. Professors used to be the primary source of expertise. Expertise is globally distributed now, reachable by anyone with a phone. Learning used to happen before work started. It happens continuously now, for the rest of a person's life. Degrees used to be the clearest signal of capability. Portfolios, real things a person has actually built, are becoming a clearer one. Standardized instruction used to be a practical necessity. Personalized learning is actually possible now. Students used to have to adapt themselves to the system. The system can finally adapt itself to the student instead.

Every single one of those assumptions shaped how colleges were built. Every single one of them just changed underneath the institutions that were built on top of them.

If AI can already handle knowledge acquisition, writing support, research, coding, and analysis, the real question becomes simple, even if the answer is not.

What should a human actually spend the next ten years of their life learning?

I think it comes down to six things, and if you have been reading this series, several of them will sound familiar, because they map closely onto the four clusters from a couple editions back.

Self-awareness. How you think, how you learn, your actual strengths and actual weaknesses, what genuinely motivates you versus what you have been told should motivate you. The first job of an education is helping someone understand their own operating system, not handing them someone else's.

Learning how to learn. Asking better questions, synthesizing information, staying adaptable as the ground keeps shifting. The most valuable skill stops being what you already know and becomes how fast you can actually learn the next thing.

Creation and building. Businesses, software, content, research, real projects with real output. A portfolio of things actually made becomes more valuable than a transcript of classes attended.

Human relationships. Communication, leadership, collaboration, empathy, the ability to actually work with other people, and now also with AI. As AI gets more capable, this cluster does not shrink in importance. It grows.

Judgment. Decision-making, ethics, systems thinking, weighing tradeoffs, staying steady inside genuine uncertainty. AI can generate the options. A person still has to decide which one actually matters.

Purpose and mission. Not "what career do you want," but "what problem do you actually want to help solve." A person anchored to a real purpose keeps learning long after any formal program ends.

None of these six get taught well by a lecture and a multiple choice test. All six require something closer to practice, mentorship, and real stakes.

Here is where I want to name the model directly, because I have been circling it for four editions now.

The AI-Native Microcollege. A small, cohort-based learning community, somewhere between ten and thirty people, combining an AI cognitive partner for every single learner, real human mentors, project-based learning instead of lecture-based learning, apprenticeships instead of purely theoretical instruction, genuine entrepreneurship, and personalized pathways instead of one fixed sequence everyone has to move through at the same pace.

Assessment does not look like the exams and essays this whole series has already pushed back on. It looks like portfolios. Demonstrations. Oral defenses, where you actually have to explain your reasoning to a real person, not fill in a bubble. Peer review. Mentor evaluation. Real-world outcomes, whether the thing you built actually worked.

This is not simply a smaller college. It is a different model, built around the six pillars instead of around a fixed curriculum designed for a world where information was still the scarce resource.

Industrial-era education was built around standardization, because standardization was the only practical way to teach large numbers of students at once with the tools available at the time.

AI makes personalization practical for the first time at scale. That creates real opportunity for dyslexic learners, ADHD learners, visual and systems thinkers, and the kind of pattern-connecting minds this whole series has been describing. Instead of forcing every student to adapt to one rigid structure, the structure itself can finally adapt to the learner.

I do not think that is a small opportunity. I think it might be one of the most significant shifts available in education in a very long time, precisely because it is the first model actually designed around cognitive difference instead of designed to quietly filter it out.

You know why.

Makena and Kailer were homeschooled. I have spent years paying close attention to microschools, Acton Academy style models, and two-hour learning approaches, not as academic interest but because I was trying to find or build something that actually fit how her brain works, instead of asking her to keep adapting to something that never quite did.

Everything in this edition is not theoretical for me. It is close to a description of what I have already been reaching toward, piece by piece, for years, before I had the language to describe the whole shape of it at once.

One thing to sit with this week.

Pick one of the six pillars and ask yourself honestly how much of your own education, or your kid's, was actually built around developing it. Not how much time was spent on it. How much of the actual structure, the assessment, the daily rhythm, was designed with that pillar as the goal.

You will probably find the honest answer is less than you'd expect, for at least a couple of them. That gap is not a personal failure. It is the shape of a system built for a different era.

Use this to figure out where the six pillars actually stand in your own life or your kid's education right now.

"Here are six pillars: self-awareness, learning how to learn, creation and building, human relationships, judgment, and purpose. Ask me questions about my current work or my child's current education, then help me honestly assess which of these six pillars are being actively developed right now, and which ones are being almost entirely ignored."

See the gap clearly. Then decide what to do about it.

Matt "Coach" Ivey

Founder, LM Lab AI | Creator, The Dyslexic AI Newsletter

Dictated, not typed. Obviously.

Edition 369: Topic coming soon. Stay tuned.