Professional Agent Development in Practice with TypeScript Bootcamp

Go Beyond the Basics: Build, Orchestrate, and Scale Production-Ready AI Agents with TypeScript and LangChain

October 29 – 30, 2026

Time until the Bootcamp starts:

Gain a complete understanding of modern agent development, from the agent loop and model configuration to tools, state management, structured outputs, and multimodal input.

Go beyond basic prototypes with middleware, context engineering, RAG, guardrails, PII detection, and Human-in-the-Loop workflows for reliable real-world applications.

Learn how to design production-ready multi-agent systems using supervisors, routing, handoffs, MCP, long-running conversations, deployment patterns, and observability.

Bootcamp Program Day 1

Agent Fundamentals

Understand the agent loop and learn how autonomous agents combine actions, observations, and context to complete complex tasks.

Models, Tools, and State

Configure models and system prompts, enforce structured outputs, connect tools, manage short-term memory, and process multimodal content such as PDFs and images.

Middleware and Context Engineering

Implement Node-style and Wrap-style middleware, transform outputs, track agent behavior, detect sensitive data, and provide models with precisely the context they need.

Bootcamp Program Day 2

Advanced Agent Workflows

Apply dynamic model and tool selection, integrate Retrieval-Augmented Generation, and introduce Human-in-the-Loop controls for critical decisions.

Multi-Agent Architecture and MCP

Design systems using subagents, supervisors, routing, and handoff patterns. Use the Model Context Protocol to connect your agents with external APIs and resources.

Production and Hands-On Development

Handle long-running conversations, improve prompts, prepare agents for deployment, and add the observability needed to operate them reliably. During the bootcamp, you will implement a fully functional multi-agent application based on the techniques covered.

Technical Requirements

- - Proficiency in TypeScript and JavaScript: A solid understanding of TypeScript and JavaScript is required for the practical exercises and agent-development examples
  - Prepared Development Environment: Bring a laptop with Node.js installed, a modern code editor such as VS Code or WebStorm, and a working TypeScript development environment
  - Curiosity and Enthusiasm for AI: An interest in AI agents, modern software architecture, and hands-on experimentation will help you get the most from the bootcamp

Who Should Attend?

- - AI Developers and Engineers: Professionals building LLM-powered applications who want greater control over agent behavior, workflows, and architecture
  - Software Developers: Developers ready to move beyond basic chatbot tutorials and build practical, production-focused AI systems
  - Full-Stack and Backend Developers: Engineers integrating agents, tools, APIs, RAG systems, and external data into existing applications
  - Software Architects and Technical Leads: Professionals evaluating multi-agent systems and looking for reliable architectural patterns for real-world projects

Why Should You Attend?

After completing this intensive bootcamp, you’ll be equipped to:

- - Build Intelligent AI Agents: Create agents that can reason, use tools, manage state, and work with different types of content
  - Control Agent Behavior: Use middleware, structured outputs, guardrails, PII detection, and context engineering to make agent workflows more predictable
  - Create Advanced AI Workflows: Combine dynamic model selection, RAG, and Human-in-the-Loop processes for more capable applications
  - Design Multi-Agent Systems: Apply subagent, supervisor, routing, and handoff patterns to distribute tasks across specialized agents
  - Deploy Production-Ready Solutions: Connect agents through MCP, manage long conversations, and apply proven engineering practices for deployment and observability

Masterclass Highlights

Complete Agent Development Journey: Explore the full process, from the foundations of the agent loop to advanced orchestration and production operations
LangChain in Practice: Understand the components beneath the framework’s abstractions and gain greater control over how your agents work
Advanced AI Engineering Techniques: Work with middleware, context engineering, RAG, guardrails, Human-in-the-Loop workflows, and dynamic agent selection
Hands-On Multi-Agent Development: Build a functional multi-agent application based on the architecture and techniques taught during the bootcamp
Production-Focused Expert Guidance: Learn practical patterns from an experienced software engineer who specializes in bridging modern AI with scalable software development

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Meet the Trainer

Nir Kaufman

Nir Kaufman is a Full-Stack Agentic AI Tech Lead at Tikal with more than two decades of engineering experience. He specializes in robust web architectures and multi-agent AI systems and is a Google Developer Expert in Web Technologies, international keynote speaker, trainer, and technical author. His work focuses on bridging the gap between modern AI technology and scalable software engineering.