Turn the customer problem into proof.
Discover a real workflow, design the right AI architecture, prove value with a working pilot, and hand it over responsibly.
- 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.
Frontier AI companies now hire dedicated applied-AI architects and solutions engineers to bridge customer problems and production systems. The planned track would combine technical building with discovery, evaluation, and client communication.
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 technical discovery and translate pain into testable requirements
- 02Choose between prompting, retrieval, tools, fine-tuning, and automation
- 03Build a secure pilot around representative customer data
- 04Define evaluation criteria, cost limits, and acceptance tests
- 05Present tradeoffs to technical and non-technical stakeholders
- 06Prepare deployment, training, documentation, and owner handoff
The proof this track would demand.
A working AI pilot for a real business with a discovery brief, architecture decision record, representative evaluation set, cost model, security notes, stakeholder demo, and production handoff plan.
The working stack.
Tools can change before launch. The proposed workflow and quality bar are the durable part.
- Python or TypeScript
- OpenAI or Anthropic API
- MCP
- Postgres
- Vercel or Cloudflare
- Evaluation tooling
Register interest in this track.
Join the track-specific waitlist. This is separate from the internship intake waitlist and does not submit an application.