Coding with AI - part 2

Description

This session provides an introduction to available AI-based tools. The first block covers why developers should care about utilizing AI in their projects, followed by a brief overview of Large Language Models (LLMs) and their role in modern development workflows. The subsequent blocks follow a well-defined progression: starting with prompting web-based applications like ChatGPT, transitioning into an Integrated Development Environment (IDE) to leverage autocomplete and chat features, and concluding with autonomous AI agents.

Participants are welcome to follow along with the live demonstrations using their own coding tools. Time is reserved to walk through the setup of freely accessible tools to encourage participants to follow along and explore during the session on Thursday morning.

1. Part 1

• Introductions and outline of what we will learn in these two 3-hour sessions Learning Objectives
  • Navigate the Ecosystem: Select the appropriate AI tool (Browser, IDE, or CLI Agent) based on the context required for the task.
  • Control the Chaos: Engineer deterministic workflows using markdown plans to constrain agents and prevent hallucination loops.
  • Protect Your Data: Deploy local, offline models to utilize AI assistance without violating academic or proprietary data compliance.
• Large Language Model Background Information
• Demonstration using web-based LLM interface (Gemini, Claude, or ChatGPT)

2. Part 2

• Introduction to Interactive Development Environments (IDE) with AI capabilities
• Specific walkthrough of VSCode
• Demonstration of Autocomplete and Chat features within the IDE

3. Part 3

• Introduce background information on agents
• Demonstration of how to use AI agents
  • Implement, optimize, and benchmark a program centered around the number of ways a_n can be written as the sum of distinct positive perfect squares.
  • Implement a graph building application with a graphical user interface to demonstrate agentic-AI capabilities.