University of College (UofC)

UofC is a client-driven AI engineering incubator where teenagers learn by building useful software with real small businesses.

The model combines three things:

1. Education: students learn product discovery, AI-assisted software development, deployment, and customer success.
2. Small-business service: owners receive lightweight tools that remove specific operational bottlenecks.
3. A compounding product engine: repeated client problems become reusable modules, shared infrastructure, and eventually scalable products.

UofC is not primarily a lecture course, a resume-building exercise, or a generic software agency. Its unit of learning is a real client problem carried from conversation to a maintained production tool.

Working thesis

Teenagers can become capable, responsible AI product builders by serving real people, while small businesses gain access to software that would otherwise be too costly or too generic.

The intended flywheel is:

Listen to one business → prototype a solution → deploy and support it → identify the repeated pattern → reuse the solution across a vertical → teach the next student team

Repository map

• docs/01-foundation.md — mission, positioning, principles, and strategic boundaries
• docs/02-incubator-operating-model.md — roles, workflow, curriculum, safety, and capacity assumptions
• docs/03-home-schooled-podcast.md — the podcast concept and repeatable episode format
• docs/04-berea-opportunity-map.md — initial small-business wedges in Berea
• docs/05-90-day-launch-plan.md — a sequenced path from source material to a working pilot
• docs/06-open-decisions.md — choices that should be resolved before scaling
• docs/curriculum/README.md — the 12-week Tactical AI Skills Core Curriculum and teaching index
• projects/README.md — client-project portfolio and documentation register
• relationships/README.md — lightweight relationship CRM
• research/source-index.md — provenance, source quality, and imported source files
• data/berea-small-business-ai-opportunities.csv — the supplied opportunity matrix and public contact details
• .agents/skills/prototype-discovery-client-onboarding/SKILL.md — converts discovery evidence into an approved prototype scope and onboarding handoff
• .agents/skills/prototype-implementation/SKILL.md — repository-local agent skill for building scoped clickable prototypes

Repository-local agent skills

Agents that support repository-local skills can discover both skills after cloning this repository and opening the UofC checkout.

Start after a client discovery meeting:

Use $prototype-discovery-client-onboarding to turn these discovery materials into a prototype scope and implementation handoff.

Then implement the approved handoff:

Use $prototype-implementation to build the approved prototype scope.

Together, the skills preserve source traceability, distinguish approved work from assumptions, track onboarding truthfully, enforce a frontend-only mock-data boundary, and require honest limitation labeling and an unambiguous preview destination.

Current state

The supplied material documents an early live pilot, a proposed operating structure, five Berea opportunity categories, a broader community-revitalization thesis, and the creative direction for a companion podcast. Operational handoffs now index Land and Earn, CME Atlas, and FundGuide as separate products with pinned source history, deployment identity, technical evidence, and remaining production gates. Capacity, pricing, legal structure, child-safety policy, and shared platform architecture remain hypotheses until validated.