Learn the applied-LLM stack the way you'll actually be interviewed on it: framework-free, on a free API, from prompting all the way to serving, fine-tuning, and a red-team benchmark. Runnable Colab notebooks for the AI Engineer / Forward Deployed Engineer (FDE) skill set. You build working systems on top of foundation models (model APIs, RAG, evals, agents, adaptation, serving) using raw APIs, not frameworks. What makes this different Framework-free, on purpose. You write the agent loop, RAG, and evals from raw API calls first, so you understand what LangChain/LlamaIndex actually do before you reach for them (and can judge when not to). Patterns are durable; wrappers churn. Evals are the spine. "Measure before you tune" is installed early and returns in every section. It's the habit that separates an engineer who shipped a system from one who built a demo. Free to run, end to end. Everything runs on the free Groq API (no credit card).…