04Mentors
Mentors lead modules, run project reviews and write field notes. Every profile on this page is a fictional sample for this template — replace names, bios and photos with your own instructors.
Sample profileLLM Application Engineering
Alex focuses on the unglamorous parts of LLM products: input validation, structured outputs and graceful failure. Their sessions are about turning a promising prototype into code a team can maintain.
Sample profileRAG & Knowledge Systems
Priya teaches retrieval-augmented generation from the data up: parsing, chunking, retrieval and the evaluation that tells you whether any of it is working.
Sample profileEvaluation & AI Reliability
Jordan teaches how to know whether an LLM feature is good enough to ship — and how to notice when it stops being good enough.
Sample profileDeployment & LLMOps
Sam covers what happens after the demo works: packaging, deployment, tracing, cost control and the operational habits that keep LLM services predictable.
Sample profileAI Agents & Workflows
Maya teaches agent design as workflow engineering: well-scoped tools, explicit state, clear stopping rules and a plan for every way a step can fail.
About these profiles
Names, photos and bios are placeholders. Mentor data lives in src/data/mentors.ts and portraits in src/config/assets.ts.
Build the foundations, projects, and habits needed to design more dependable AI applications.