Build fast. Understand every decision.
Use AI coding tools to ship faster, then prove the product is secure, tested, maintainable, and worth operating.
- In planning
- No launch date is promised
- Remote-first
- Proposed delivery format
- Practical proof
- Capstone-led curriculum design
- Interest only
- Not an internship application
Why this belongs on the roadmap.
AI-assisted development changes the speed of software work, not the need for engineering judgment. This track is planned around the moment after generation, when a builder must read, test, secure, and own the result.
Research sources support the direction, not a launch date or outcome. This page does not promise a job, salary, client, income, or final curriculum.
Research basis
The work this curriculum would cover.
Each planned module is designed to produce evidence, moving from foundations to work a real operator can inspect.
- 01Turn a product brief into a working application with traceable decisions
- 02Read and explain code produced by an AI coding tool
- 03Model data, authentication, sessions, and permissions deliberately
- 04Use tests and static analysis to find generated defects
- 05Review dependencies and common web security risks
- 06Refactor, document, deploy, and monitor a maintainable release
The proof this track would demand.
A live product built substantially with AI tools, accompanied by prompt and decision logs, fixed security findings, automated tests, a documented refactor, production monitoring, and an architecture handoff.
The working stack.
Tools can change before launch. The proposed workflow and quality bar are the durable part.
- Lovable
- Replit
- Claude Code
- Cursor
- GitHub Actions
- Semgrep
- OWASP ZAP
- Vercel
Register interest in this track.
Join the track-specific waitlist. This is separate from the internship intake waitlist and does not submit an application.