# Bootstrap Job Tutor Platform

## Summary

Create the first product baseline for a web-based AI tutor aimed at software job
seekers. The platform uses workflow-driven technical interview practice,
structured learner memory, and source-backed ontology building from uploaded
learning materials.

## Why

Software job seekers need adaptive practice and evidence-backed feedback more
than another generic interview-question list. A narrow first audience lets the
platform prove diagnosis, tutoring, memory extraction, and review planning
before expanding to broader student use cases.

## Motivation

The first product target should be narrow enough to build and evaluate:
developers preparing for technical interviews. This target naturally exercises
adaptive questioning, answer grading, misconception tracking, review planning,
and material-to-curriculum transformation. The same foundation can later expand
to general students.

## Scope

- Define the job-seeker-first product direction.
- Define learner memory requirements.
- Define ontology ingestion and gap-detection requirements.
- Define workflow boundaries for `agent-farm-go` and `third-one`.
- Define generated visual teaching asset requirements.

## Non-Goals

- Implement the full web service in this change.
- Replace a school LMS.
- Build a marketplace or certification product.
- Treat generated ontology content as canonical without review.

## Impact

This establishes the planning baseline for future implementation. Future code
changes should trace back to these specs and keep OpenSpec updated as the
product shape evolves.