Short, focused courses on retrieval, reasoning, and production AI — built for engineers who want to go beyond the tutorials.
Query transformation, sparse and dense retrieval, reranking, fusion, chunking, and production patterns — the full retrieval stack.
System topology, Pub/Sub, Cloud Functions, API Gateway, and BigQuery cost controls — the architectural patterns behind production serverless pipelines on GCP.
Evals, tracing, regression testing, and monitoring LLM systems in production — the discipline that separates demos from products.
CoT, self-consistency, tree of thoughts, and structured reasoning — when and how to use each to improve LLM output quality.
Tool use, planning, memory, multi-agent coordination, and evaluation — everything you need to ship agents that actually work.