Choose the right AI problem.
Find a valuable problem, define the system and its failure boundaries, then ship and measure a useful AI product.
- 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 product work joins customer discovery with model behavior, evaluation, data, and launch judgment. Current frontier-AI product roles explicitly connect user needs to model decisions, measurement systems, and reliable deployment.
Research sources support the direction, not a launch date or outcome. This page does not promise a job, salary, client, income, or final curriculum.
The work this curriculum would cover.
Each planned module is designed to produce evidence, moving from foundations to work a real operator can inspect.
- 01Run customer discovery and separate a real problem from an AI-shaped solution
- 02Define success, failure modes, and non-goals before building
- 03Write product requirements that cover data, evaluation, and human review
- 04Prioritize model, workflow, and interface tradeoffs
- 05Instrument adoption, quality, cost, and user outcomes
- 06Lead a launch review and write an evidence-based retrospective
The proof this track would demand.
An AI product or feature shipped for a real business with discovery evidence, a decision-ready PRD, evaluation criteria, acceptance tests, launch instrumentation, an outcome memo, and a clear retrospective.
The working stack.
Tools can change before launch. The proposed workflow and quality bar are the durable part.
- Claude
- Jira Product Discovery
- Figma
- PostHog
- A build stack of your choice
Register interest in this track.
Join the track-specific waitlist. This is separate from the internship intake waitlist and does not submit an application.