AI Stack for Developers

Three intensive coding days to ship production AI apps: RAG, agents, light fine-tuning, evals, observability. OpenAI + Anthropic + open source.

Access

Terms shared on request

Program

LLM architectures: RAG vs fine-tuning vs prompting

Stack: LangChain, LlamaIndex, vector DBs (pgvector, Pinecone)

Agents: tool use, MCP, frameworks (LangGraph, CrewAI)

Evals & observability (LangSmith, Braintrust)

Cost, latency and streaming in production

Capstone project: deploy a specialized AI assistant

Node.js or Python experience. Familiarity with REST APIs and Git.

Terms shared on request

Terms shared on request

Terms shared on request