Status: First draft for review. These answers describe the proposed model, not an operating institution or an offer of admission.
1. What is my child actually preparing for?
Professional work in a world where AI is available. The aim is to develop judgment, professional depth, experience, and relationships alongside the ability to direct and challenge AI.
Students should leave with work they can show, decisions they can explain, and people who can speak to their contribution. The model brings early professional experience into college.
2. What if they do not know what they want to do?
They need a purpose worth exploring, but they do not need to choose a degree program at the outset.
In Year One, an advisor helps translate that purpose into an exploration plan. Departmental placements introduce different fields and help the student choose where to develop professional depth. The plan can change as the student learns.
The student Q&A also makes an honest commitment: someone without an interest or concern worth pursuing may benefit from time to work and explore before paying for university.
3. How will you know they are learning rather than letting AI do the work?
A finished assignment is insufficient evidence of understanding. Students apply ideas, explain their reasoning, teach others, and respond to questions or changed conditions.
AI stays available during assessment. Faculty judge the student's understanding and responsibility for the result. Gaps lead to further practice and reassessment. The precise assessment procedures and standards remain operating design work.
4. Will they still have professors and a campus community?
Yes, those human relationships are central to the proposal. A continuing pod and mentor provide a starting community. Faculty guide subject learning, challenge applications, and assess understanding.
Individual study supports discussion, laboratories, creative work, teaching, and collaboration. Campus life, visiting experts, and work across disciplines broaden the student's relationships. Staffing arrangements and physical campus requirements remain to be established.
5. Is this only for students who want to start a company?
No. Capstone corporations create a setting where different specialists work together with real responsibilities.
A student may contribute as an engineer, designer, researcher, operator, or another professional. Forming and directing an organization is part of the experience, but every student does not need to pursue entrepreneurship after graduation.
6. What happens if their team or company fails?
A company's commercial outcome and a student's development are different things. The institution's responsibility is to keep meaningful learning and professional work available.
The working model proposes university-supported instructional capital for a Builder Year when outside funding does not materialize. That support would provide an opportunity to finish the educational work; it would not demonstrate commercial viability.
How students move between struggling organizations, how support is funded, and how assets are handled at dissolution still require design.
7. Will employers recognize what they leave with?
The proposal makes capability visible through attributable work, responsibilities, references, and demonstration on a new problem. Employers can inspect what the graduate has done and watch how they work with their agents.
Employer recognition still needs to be tested. The institutional form, accreditation path, and relationship to conventional credentials remain unresolved. Families should be able to inspect those arrangements before making an enrollment decision.
8. How much will it cost, and is there financial aid?
Tuition, financial aid, and a complete funding model have not been established.
AI-supported instruction could change institutional costs, but the model also depends on mentors, laboratories, professional networks, and meaningful work. A credible price must account for those commitments. There is no published tuition or financing offer in this proposal.
9. Who owns their work and their personal AI context?
The intended outcome is that graduates retain the accumulated personal working context and agent force developed alongside their education.
The operating rules must distinguish personal learning history, independently attributable inventions, company work, and confidential partner information. Ownership, licensing, portability, permissions, and the student's ability to correct the record remain explicit design questions.
10. Does this guarantee a job or a successful company?
No. The proposed commitment is access to instruction, mentors, tools, laboratories, networks, and meaningful work.
Students remain responsible for their effort, initiative, judgment, and contribution. Employers make hiring decisions; customers and funders determine commercial outcomes. The model must be evaluated through what students actually become capable of doing.