1.6 KiB
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-goandthird-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.