The Great Unbundling: Why Self-Directed Mastery is the New American Education

America stands on the precipice of a quiet yet absolute educational revolution. For decades, the national discourse has centered on fixing a broken system, yet we must acknowledge a fundamental economic reality: large-scale education systems, often managed by government bureaucracies, possess almost no incentive to change. These institutions are infected by what those in Positive Political Theory call congealed preferences. Like wet cement that has long since hardened, the incentives and constraints of these monoliths are designed for stasis, not evolution (Riker, 1980). This phenomenon is not unique to education; it is a hallmark of entrenched bureaucracy, often manifesting as a "Concrete Curtain" that protects the status quo for the few at the cost of the many (Hulett, 2025).

Expecting these systems to reform from within is a strategic error. Instead, the revolution is occurring as better, smaller systems emerge outside these congealed structures. The monoliths will not change; they will simply dwindle as students and families—the true customers of education—vote with their feet. Eventually, these systems will shutter not because of a policy shift, but because no one shows up.

This article explores how this transition occurs by examining personal experiences, case studies, and cutting-edge research. We will discuss the impact of "flipping the classroom" and the pedagogical mirror facilitated by AI. Ultimately, school systems possessing the leadership to prioritize improvement will join this revolution, while those tethered to the status quo will descend into irrelevance.

About the author:  Jeff leads Personal Finance Reimagined, a decision-making and financial education organization. He teaches personal finance at James Madison University and provides personal finance seminars. Check out his book -- Making Choices, Making Money: Your Guide to Making Confident Financial Decisions.

Jeff is a career banker, data scientist, behavioral economist, and choice architect. Jeff has held banking and consulting leadership roles at Wells Fargo, Citibank, KPMG, and IBM.

The Self-Directed Bedrock of Education

Let us start with what education is actually doing in the information age. We do not need to teach facts and formalizations because school and teachers are the only places where they can be obtained. Of course, all humans need "language acquistion" as a means to stimulate the language centers of young brains. But do we need teachers to be the providers of those facts and formalizations when they are readily available because of the information age? Not anymore. In the information age, a much more effective and powerful role for teachers is to teach students how to acquire those facts and formalizations with the objective to facilitate student self-learning. In the information age, teachers are the facilitators of the language acquisition process, not the source of those facts and formalizations.

Education credentials serve as the bedrock of professional authority, yet education's most potent form exists at the intersection of formal rigors and self-directed inquiry. My academic journey began with a focus on finance and economics during my undergraduate years, followed by a Master's of Economics. This formal training provided the educational scaffolding necessary for understanding market dynamics and incentive structures. Also, my credentials helped me get my first job. Post-graduate coursework in mathematics further sharpened these analytical tools, creating a robust framework for interpreting complex systems.

While formal credentials provide a necessary signal of competence for the labor market, the motivation, confidence, and achievement of self-learning form the true bedrock of becoming educated. My credentialed education provided a starting point, helping me get a job, but it is the self-learning approach to my life that enabled the true learning necessary for success. This internal drive transforms a passive student into an active architect of knowledge. Formal education offers the map; self-learning empowers the individual to explore the terrain with purpose and depth.

The Neurological Rewards of Mastery

The achievement of mastering a new skill independently triggers specific neurological rewards. Neurotransmitters like dopamine and oxytocin play a vital role in social motivation and the reinforcement of learning habits. When an individual successfully navigates a demanding challenge through self-study, the brain releases dopamine, signaling a reward and encouraging further intellectual exploration. Positive feedback from bosses or peer groups further reinforces the learning process.  (Hulett, 2023) This cycle builds the confidence necessary for tackling increasingly complex problems.

Economic principles like comparative advantage also apply to self-learning. In my case, this self-directed approach enabled the rapid acquisition of deep understanding and technical knowledge in programming, banking, and data science. While credentials often serve as employment signals, the true value of education lies in the specialized understanding enabled by self-directed inquiry. Everyone has the opportunity to find their high-impact niche and to evolve that niche as the market evolves.

Building the Machine: A Case Study in Understanding

During my 20s, the personal computing revolution began with the Intel 8088 and 286 microprocessors. Rather than relying on classroom instruction, I chose to build a computer from individual components to demystify the technology. This experience served as a practical laboratory for understanding hardware-software interfaces. Building the machine and learning machine language provided a level of insight no lecture could replicate, grounding abstract concepts in physical reality.

This builder mindset became the catalyst for my professional evolution. It moved the focus from mere data collection to the creation of decision frameworks. Self-learning requires a high degree of human oversight and judgment—the same qualities required for managing AI-augmented systems effectively today. This period taught me the world remains complex, requiring constant adaptation rather than reliance on static knowledge.

Building the Road: The Evolution of Behavioral Economics

My early professional training mirrored the birth of Behavioral Economics. At the time, the discipline lacked formal definition, requiring us to blend classical economic theory with behavioral psychology manually. We were effectively building the road while walking it. We recognized human cognition as a primary variable in economic outcomes, moving beyond the rational actor models prevalent in traditional classrooms (Thaler, 2015).

This era relied heavily on Randomized Control Trials (RCTs). By executing thousands of RCTs in the banking sector, we used the tools of science to validate our self-taught hypotheses. These trials helped us manage risk and drive client delight while maintaining profitability. The scientific method provided the evidence-based foundation needed for turning intuition into a scalable strategy.

To be clear, I am no more special than anyone else. I was a "try-hard" student motivated by fear of not making my parents or bosses happy, but no more gifted than any other student. I will say, the greatest gift my parents gave me was the permission and expectation to be curious. They allowed me to go down rabbit holes. They allowed me to fail and try again.

Writing as the Ultimate Thinking Tool

For years, I viewed writing as a task to outsource, often claiming I lacked proficiency as a writer. I thought of myself as a "Mathy Guy," not a "Man of Letters." However, I’ve come to appreciate David Bessis’s insight in Mathematica—that math is essentially a formal language for the things we cannot easily see or touch. I quickly realized that math and prose are merely different lenses for the same clarity of thought; both require the discipline of translating internal intuition into external logic.

I eventually realized that the acceptance of being a poor writer is equivalent to accepting being a poor thinker. This realization sparked a commitment to mastering the craft. Writing serves as a cognitive discipline, forcing the brain to organize fragmented data into a coherent, logical narrative. Prose demands clarity and eliminates the all-or-nothing language common in undisciplined thought. It encourages the use of active voice and precise language, mirroring the structured decision-making processes championed by Personal Finance Reimagined (PFR). My focus on writing has been greatly enhanced and accelerated by AI.

The Bridge: Technology as the Catalyst for Agency

The thread connecting my experience building computers, testing economic theories, and mastering prose is agency. In each instance, I was not a recipient of information, but an architect of understanding. Historically, this level of self-directed mastery was reserved for those with the time, resources, or unique disposition to "build the machine" themselves.

The institutional challenge we face today is that our current school systems are designed for compliance, not agency. They are built on the "Information Transmission" model, where a teacher speaks and a student listens. To move from a system of static achievement to one of continuous, emergent learning, we must provide every student with the tools to become a self-learner. This is where technology and new pedagogical models move from being "add-ons" to being essential infrastructure.

The Impending Revolution: The Pedagogical Mirror

Generative AI is fundamentally altering the path to becoming educated through the concept of the Pedagogical Mirror. This framework leverages AI to reflect a student’s current understanding back to them, identifying and correcting misconceptions in real-time (Luckin, 2018; Hulett, 2025). This mechanism creates a fast feedback loop, allowing learners to pivot and refine mental models without the delays inherent in traditional grading. By mirroring the learner’s own logic, the technology accelerates the transition from confusion to mastery.

In the near future, Artificial Intelligence will likely handle the information transmission aspect of education almost entirely. This shift allows the role of the teacher to morph into that of a high-level coach. Teachers will shepherd a portfolio of students accountable for demonstrating mastery while encouraging them to reach higher levels of achievement. Significantly, this allows our education system to break the "Tyranny of the Semester." This is where students are grouped by time (a school year) instead of mastery level. No longer will teachers need to move an entire class at the same pace. Once an individual student reaches mastery, this new model allows them to move forward. The boredom of those ahead and the frustration of those behind are resolved. Schools will become environments primarily oriented toward socialization and the cultivation of a healthy learning culture rather than the rote "doing" of education.

The Need to Scale

This approach is absolutely scalable; the only thing standing in our way is the organizations needing to adapt. "De-congealing" is difficult. Tenured teachers often have little incentive to change. Clinging to the "way we have always done it" is clinging to a comfortable approach requiring little extra work. Typically, school systems do not reward teachers or administrators with extra compensation for the extra work required for change. Therefore, nothing changes—that is, until their schools slowly waste away.

Sal Khan, the founder of Khan Academy, has long championed this evolution. He notes: “The idea of flipping the classroom is to have the lectures at home and the homework at school, where the teacher is available to help” (Khan, 2012). This vision is more likely than ever to become a baseline reality. My wife, Patti Hulett, already exemplifies this model in her work as a tutor and life coach. She uses GenAI to provide supplementary lessons, but her superpower involves teaching a love for learning, fostering confidence, and maintaining accountability. Patti is testing the very model schools must replicate at scale to remain relevant in a post-AI world.

Thawing the Monolith: A Path for Progressive Leadership

While "congealed preferences" present a formidable barrier, there is a hopeful path forward for the progressive administrators who find themselves operating within these systems. These leaders recognize that the "way we’ve always done it" is no longer sufficient, but they also face the daunting task of innovating within a government-based structure that rarely rewards the extra effort required for change. The challenge is navigating varying levels of institutional hardness—where tenured incentives and rigid budgeting can stifle even the best intentions.

The typical concern for school systems is introducing technology, like AI, that is abused by the students in some way. Naturally, technologies need to be implemented with teacher training and safety protocols. But these newer technologies must be implemented.

Why is this implementation so urgent? Because Generative AI and related efficiency technologies are quickly becoming employment table stakes. In the modern economy, those better prepared for this reality are significantly more likely to be successful. What experience teaches us is that school systems reluctant to update technology face being responsible for accelerating economic inequality. This occurs because wealthy parents will fill the gaps with private tutors and resources, whereas less affluent families will not. This gap in preparation creates a divergence in career readiness that accelerates a cycle of social inequality. Schools should be a force for social good, not an enabler of social inequality.

The path forward lies in establishing a "North Star" anchoring the community to shared values while allowing the methods to evolve. As one forward-thinking superintendent recently noted, a strong vision for graduates "provides a north star to which we all aspire in our shared purpose... the foundation upon which we build an ever-evolving learning environment" (Byrne, 2025). By focusing on these core competencies—critical thinking, creativity, and empathy—leaders can begin to "de-congeal" their systems from the inside. The goal isn't necessarily to dismantle the school, but to modernize it, creating a space where innovation can thrive despite institutional inertia.

PFR: A Framework for Lifelong Success

The Personal Finance Reimagined (PFR) ecosystem integrates these lessons into a structured framework. Whether conducting three-credit hour classes and seminar series at universities like GMU and JMU, or implementing our curriculum and technology in high schools across the Commonwealth of Virginia, the objective remains the same: empower individuals through better decision systems.

Education, when built upon a foundation of self-learning and augmented by technology, enables individuals to find success in both their careers and their personal wealth-building strategies. By leveraging tools like the Definitive Choice smartphone app, individuals can apply the rigor of a behavioral economist to their daily lives. We encourage a view of education as a continuous, emergent process rather than a static achievement. Success is an outcome of consistent, evidence-based choices rather than luck.

Resources for the Curious

• Bessis, David. Mathematica: A Fresh Look at Mathematics. Princeton University Press, 2024. Explores math as a tool for mental discipline and understanding abstract systems.

• Byrne, Eric. “The Darien Difference.” Darien Public Schools Newsletter, 2025. Defines the "Vision of the Graduate" as a guiding foundation for evolving learning environments.

• Hulett, Jeff. Making Choices, Making Money. The Curiosity Vine, 2023. Outlines a structured decision-making framework leveraging behavioral science and economics for personal finance.

• Hulett, Jeff. “Behind The Concrete Curtain: How Zoning Benefits the Few at the Cost of the Many.” The Curiosity Vine, 2025. Discusses congealed preferences and institutional stasis in the context of land use and housing.

• Hulett, Jeff. “The Pedagogical Mirror: AI and the Future of Learning.” The Curiosity Vine, 2025. Explains how AI-driven feedback loops accelerate mastery by reflecting a learner's cognitive process.

• Kahn, Sal. The One World Schoolhouse: Education Reimagined. Twelve, 2012. Proposes a model for flipping the classroom to focus on mastery-based learning and human interaction.

• Kahneman, Daniel. Thinking, Fast and Slow. Farrar, Straus and Giroux, 2011. Explains the cognitive biases and dual-system thinking processes affecting human decision-making.

• Luckin, Rose. Machine Learning and Human Intelligence: The Future of Education for the 21st Century. UCL Press, 2018. Describes AI as a reflective tool revealing hidden aspects of the learner’s cognitive process.

• Riker, William H. “Implications from the Disequilibrium of Majority Rule for the Study of Institutions.” American Political Science Review 74, no. 2 (1980): 432–47. Explores the concept of "congealed preferences" and institutional stability in Positive Political Theory.

• Thaler, Richard. Misbehaving: The Making of Behavioral Economics. W. W. Norton & Company, 2015. Chronicles the historical development of behavioral economics and its impact on modern financial theory.