# Building functional AI agents using LangChain Day2 Lab

> In this lab, Zach dives into deep research agents and MCP tools. He explores the GitHub agent and its functionality, including how to manage pull requests and create issues on Linear. He demonstrates how to refine the agent's prompts to ensure it uses the correct tools and avoids confusion. He also…

- Web page: https://www.dataexpert.io/lesson/buildingfunctionalaiagentsusinglangchainday2lab-mar26-p737-l2140
- Program: [AIExpert](https://www.dataexpert.io/program/ai-expert)
- Module: Week 1: Prompt Engineering & Basic RAG
- Access: Requires enrollment in AIExpert
- Length: 1 h 3 min video
- Skills: Python, MLOps, LLMs, APIs
- Academy: DataExpert.io Academy

## About this lesson

In this lab, Zach dives into deep research agents and MCP tools. He explores the GitHub agent and its functionality, including how to manage pull requests and create issues on Linear. He demonstrates how to refine the agent's prompts to ensure it uses the correct tools and avoids confusion. He also introduces the deep research agent that utilizes web searches and saves findings to Supabase, emphasizing the importance of semantic matching to avoid duplicate research.

## Navigation

- Previous lesson: [Building functional AI agents using LangChain Day2 Lecture](https://www.dataexpert.io/lesson/buildingfunctionalaiagentsusinglangchainday2lecture-mar26-p737-l2139.md)
- Next lesson: [RAG optimisation + Reranking Day 1 Lecture](https://www.dataexpert.io/lesson/rag-optimisation-reranking-day1-lecture-oct-2025-p737-l1510.md)