Track · 2 courses · 0 complete
AI
Two complementary disciplines: building production AI apps in the cloud (evals, tracing, cost controls, secure-by-default egress) and owning the local metal (serving, quantization, throughput, and proving a model is safe before it ships). Engineering, not vibe-prompting.
AI Scaffolded
AI Product Engineering
Take an AI feature from "prompt in a playground" to a shipped, monitored, cost-bounded production surface — correct, observable, and secure-by-default.
~/ai-product-engineering view →
AI Scaffolded
Local LLM & Model Ops
Run, serve, evaluate, and promote local models to production on consumer GPUs — pick the right quant, squeeze throughput, build local RAG, and prove a model is safe before it ships.
~/local-llm-modelops view →