AI Application Engineering

Five-Day Intensives

• LLM Application Development with Python (35 hours delivered over 5 days, online)

  A 5-day intensive on end-to-end LLM application development in Python: model APIs, prompt pipelines, structured outputs with Pydantic, tool calling, streaming FastAPI services, RAG essentials, evals, observability, and production deployment.

• Building AI Agents with Python and MCP (35 hours delivered over 5 days, online)

  A 5-day intensive on building production AI agents in Python: agent loops, LangGraph and Pydantic AI, building MCP servers and clients, multi-agent orchestration, agent evals, security guardrails, and running open-weight models locally for restricted environments.

Building AI-Powered Applications

• LLM Application Development with TypeScript and Python (14 hours delivered over 2-3 days, online or on-site)

  End-to-end LLM application development using TypeScript and Python: prompt pipelines, tool use, streaming, structured output, and production deployment.

• Production RAG Systems for Engineering Teams (14 hours delivered over 2-3 days, online or on-site)

  Building production-grade retrieval-augmented generation systems: chunking, hybrid search, reranking, evaluation harnesses, and deployment.

• Designing Multi-Agent Systems (14 hours delivered over 2-3 days, online or on-site)

  Orchestration patterns, planner/worker architectures, agent hand-offs, and failure recovery for production multi-agent systems.

• Voice and Multimodal AI for Developers (14 hours delivered over 2-3 days, online or on-site)

  Real-time voice APIs, vision, document understanding, and multimodal application patterns for software engineers.

Tools, Skills, and MCP

• Model Context Protocol (MCP) for Developers (7 hours delivered over 1-2 days, online or on-site)

  Building and consuming MCP servers to extend coding assistants with internal tools, data sources, and APIs using the Model Context Protocol standard.

• Building Custom Tools and Skills for AI Coding Agents (7 hours delivered over 1-2 days, online or on-site)

  Function calling, tool design, and safe execution sandboxes for extending AI coding agents with custom capabilities.

Quality and Operations

• Evaluating AI Coding Assistants and LLM Apps (7 hours delivered over 1-2 days, online or on-site)

  Eval harnesses, regression suites, and golden datasets for measuring and improving AI coding assistant and LLM application quality.

• LLM Observability and Cost Engineering (7 hours delivered over 1-2 days, online or on-site)

  Tracing, token budgets, caching, and prompt versioning for production LLM applications that are observable and cost-controlled.