Software Developers

9:00 - 9:15 | Welcome & Orientation

• • Welcome & instructor introductions
• • Course overview & objectives
• • Logistics (breaks, lunch, bathrooms, WiFi)
• • Hybrid format expectations
• • In-person: Participation guidelines
• • Virtual: Camera on/off policy, chat usage
• • Icebreaker: Quick poll
• • What's your development focus? (Frontend, backend, full-stack, mobile, DevOps, etc.)
• • AI experience level (1-10)
• • One AI concern you have about software development

9:15 - 9:45 | What is AI?

• • What is AI, really? (demystified)
• • AI is not magic (it's pattern matching)
• • AI vs ML vs LLM (hierarchy)
• • Three types of AI (overview)
• • Predictive
• • Generative
• • Agentic
• • Common misconceptions debunked
• • When AI helps vs. when it doesn't

9:45 - 10:15 | Predictive AI Deep Dive

• • Predictive AI explained (weather forecasting analogy)
• • How it works (simplified - no math!)
• • Real-world examples:
• • Netflix recommendations
• • Spam detection
• • Credit card fraud detection
• • **For YOUR work:**
• • Bug prediction: Which files are most likely to contain defects after a change?
• • Code quality scoring: Predicting technical debt and maintenance burden
• • Deployment risk assessment: How likely is this release to cause incidents?
• • Performance regression prediction: Will this PR degrade response times?
• • Dependency vulnerability forecasting: Which packages are likely to have CVEs soon?

10:15 - 10:45 | Generative AI Deep Dive

• • Generative AI explained (creative AI)
• • How LLMs work (simplified)
• • Training on massive text
• • Pattern recognition
• • Next-word prediction
• • Real-world examples:
• • ChatGPT
• • GitHub Copilot
• • AI writing assistants

10:45 - 11:00 | Setup Verification & Break Prep

11:30 - 11:40 | Lab 1 Introduction

• • Lab 1 overview: "Your First AI Conversation - Developer Edition"
• • Learning objectives:
• • Chat with AI model about development topics
• • Write effective developer-focused prompts
• • Understand parameters
• • Recognize hallucinations in library and package claims
• • Demo: Instructor walkthrough (5 min)
• • Q&A (3 min)
• • Get started!

11:40 - 12:10 | Lab 1: Your First AI Conversation

12:10 - 12:25 | Lab 1 Debrief & Discussion

12:25 - 12:55 | Agentic AI & Introduction to Agents

• • Agentic AI explained
• • Chatbot (passive) vs Agent (active)
• • Example: Developer asking "how to fix this bug" vs AI agent analyzing code, running tests, and suggesting a targeted fix
• • Components of an agent:
• • Goal
• • Reasoning
• • Tools
• • Action
• • Result
• • Modern tooling: MCP (Model Context Protocol) for standardized tool integration

12:55 - 1:20 | Prompt Engineering Workshop

1:20 - 1:30 | Week 1 Wrap-Up & Homework

• • Recap: What we learned today
• • Three types of AI
• • How to use Generative AI for development tasks
• • Prompt engineering basics
• • Preview: Next Saturday (tease exciting content)
• • Build a developer knowledge base RAG system with YOUR architecture docs
• • Create your first code review agent
• • Real development productivity cost analysis