Project: Research Assistant Agent

Project: Research Assistant Agent

This is a project-based lesson where you'll apply everything you've learned to build a real AI agent system.

Project Overview

Project: Research Assistant Agent challenges you to design, implement, and test a complete AI agent. This is where theory meets practice.

Requirements

• Apply agent architecture patterns from Module 3
• Implement using tools from Module 4
• Follow production best practices from Module 5
• Document your design decisions

Project Structure

project/
├── src/
│   ├── agent.py          # Main agent logic
│   ├── tools/            # Custom tools
│   ├── memory/           # Memory management
│   └── config.py         # Configuration
├── tests/
│   ├── test_agent.py     # Unit tests
│   └── test_tools.py     # Tool tests
├── docs/
│   └── design.md         # Design document
└── README.md

Deliverables

1. Working code — A functional agent that handles the specified use case
2. Tests — Unit and integration tests demonstrating correctness
3. Documentation — Design decisions, architecture diagram, setup instructions
4. Demo — A short recording or live demo of the agent in action

Evaluation Criteria

Criterion	Weight
Architecture & Design	25%
Implementation Quality	25%
Functionality	20%
Testing	15%
Documentation	15%

Getting Started

1. Read the full requirements carefully
2. Sketch your architecture before coding
3. Start with the simplest working version
4. Iterate and add features incrementally
5. Write tests as you go
6. Document your decisions