Build a Small Language Model From Scratch
Build and inspect a small one-block transformer and its complete local training and generation path.
Building Agents with Google ADK 2.0
Build agents, tools and multi-step workflows with Google ADK 2.0, then evaluate them.
Retrieval-Augmented Generation (RAG)
Build developer-document search with LangChain and pgvector, then answer from retrieved text and charts with checked source references.
Model Context Protocol (MCP)
Implement, test and secure MCP servers and clients, from stdio to a remote OAuth-protected service with scoped database access.
Context and Memory Engineering for AI Agents
Assemble bounded model requests, compare context policies and maintain scoped memory with explicit provenance, retention and deletion rules.
LLM Evals
Test LLM features with pytest and DeepEval, measure RAG and tool-call quality per stage, and gate prompt, model and dataset changes on regressions in CI.