Workshop 04 - Morning Session: Specialised AI Agents

Build Your AI Workforce

Welcome to the most hands-on session of the programme. Over the next 3 hours, you will move beyond chatting with AI and start deploying specialised agents that reason, use tools, and complete complex tasks autonomously. By the end of the morning you will have built working agents for research, code review, content creation, and task planning -- and you will understand the production-grade patterns behind them.

What You Will Build

• Tool-Using Agent -- a Claude API agent that calls external tools via structured function calling
• Claude Code Workflow -- a multi-step coding agent configured with CLAUDE.md and MCP servers
• Research Agent -- an autonomous web-research pipeline with source tracking and citations
• Multi-Agent Pipeline -- coordinated specialist agents (researcher, writer, editor) collaborating on a single deliverable

Each project is progressive: later exercises build on patterns introduced in earlier ones, so work through them in order.

Chapter Navigation

1. Introduction -- Agent Landscape and Architectures (15 min)

   • What makes 2025-2026 agents different from chatbots
   • The ReAct pattern: reasoning plus acting
   • Real-world agent applications across domains

2. Core Concepts -- Tools, MCP, Agent Patterns, and Frameworks (45 min)

   • Claude Code as a production coding agent
   • Anthropic Agent SDK for custom agents
   • MCP (Model Context Protocol) -- the standard for tool integration
   • Agent architectures: ReAct, Plan-and-Execute, Subagent Delegation, Reflection
   • Memory systems and cost control

3. Hands-On Practice -- Build Your First Agents (60 min)

   • Project 1: Basic Claude API agent with tool use
   • Project 2: Claude Code as an agent (CLAUDE.md, MCP servers, subagents)
   • Project 3: Agent with memory (store and recall facts)
   • Project 4: Research agent with web search and citations

4. Exercises -- Progressive Skill-Building Challenges (30 min)

   • Weather agent with chained tool calls
   • Code review agent (complexity and security analysis)
   • Claude Code workflow with CLAUDE.md configuration
   • MCP server integration and filesystem tools
   • Task decomposition agent
   • Multi-agent content pipeline (preview)

5. Project Work -- Production Research Agent (30 min)

   • Full implementation: search, source evaluation, synthesis, citations
   • Test suite and evaluation criteria
   • Stretch goals: model routing, parallel search, fact-checking

6. Assessment -- Knowledge Validation (15 min)

   • Conceptual questions on architectures and MCP
   • Code analysis and bug-spotting
   • Agent design and safety scenarios
   • Practical mini-agent implementation (bonus)

7. Additional Resources -- Tools, Libraries, and References

   • Official documentation links (Anthropic, MCP, LangChain)
   • Research papers (ReAct, Toolformer, Generative Agents)
   • Development setup for Python and TypeScript
   • Community channels and newsletters

Learning Objectives

See objectives.md for detailed learning outcomes, skill progression, and success criteria.

Prerequisites

Review prerequisites.md before starting this session to ensure your environment is ready.

Key Technologies (2026)

Technology	Role in This Workshop
Claude API	Tool use with Sonnet 4.6 and Opus 4.8 models
Claude Code	Terminal coding agent with subagents, hooks, and CLAUDE.md
MCP (Model Context Protocol)	Standardised tool integration -- filesystem, GitHub, search, databases
Anthropic Agent SDK	Python and TypeScript SDK for building custom agents
OpenAI Codex CLI	Open-source terminal agent (comparison tool)
Aider	Open-source multi-model pair programming
Cursor / Windsurf	IDE-integrated AI agents
LangChain / LangGraph	Framework-agnostic orchestration and graph workflows
CrewAI	Role-based multi-agent teams

Who This Session Is For

Ideal Participants

• Professionals who have completed Phases 1-5 of the programme (or equivalent experience)
• Anyone building AI-enhanced workflows for research, analysis, content, or operations
• Team leads evaluating agent tools for their organisations
• Consultants and freelancers who want to automate specialist tasks

You Will Succeed If You

• Have basic Python or TypeScript familiarity (variables, functions, running scripts)
• Understand what an API call is
• Have used a Large Language Model (ChatGPT, Claude, Gemini) in any capacity
• Are willing to experiment and iterate

No Experience Required In

• Building AI agents or chatbots
• MCP or tool-use protocols
• Multi-agent frameworks
• Production deployment

Session Structure

Block	Duration	Activity
Introduction and Concepts	60 min	Agent landscape, tooling decision tree, ReAct pattern, MCP deep-dive
Hands-On Practice	60 min	Build four working agents (tool use, Claude Code, memory, research)
Exercises and Project	45 min	Progressive challenges and production research agent
Assessment and Wrap-Up	15 min	Knowledge check, reflection, afternoon preview

• Total Duration: 3 hours
• Format: Instructor-led live coding with hands-on exercises
• Difficulty: Intermediate to Advanced
• Ratio: 60% hands-on, 40% concepts

Connection to the Afternoon Session

This morning focuses on individual specialised agents. The afternoon session (Workshop 04 Afternoon) builds on these foundations to cover:

• Multi-agent orchestration and subagent delegation
• Claude Code workflow pipelines
• Safety guardrails, cost control, and human-in-the-loop patterns
• Production deployment with monitoring and logging

Everything you build this morning carries directly into the afternoon.

Quick Readiness Check

• Python 3.10+ or Node.js 18+ installed
• Anthropic API key set in your environment
• Terminal or VS Code integrated terminal open
• 3 hours of focused time blocked
• Real project or research topic in mind
• Read through the prerequisites

Getting Started

Start with the Introduction -->

Or jump directly to:

• Core Concepts -- the tooling decision tree and agent patterns
• Hands-On Practice -- start building immediately
• Prerequisites -- verify your setup
• Objectives -- see exactly what you will learn