2027 Edition · Lecture slides

Slides, your term.

Full 20-slide decks built for ~3 hours of lecture a week, then automatically trimmed to fit a quarter or an intensive summer. Click any slide to read it full-size.

Textbook Suggested labs Syllabus

The .pptx matches your selected term below, opens in PowerPoint and imports into Google Slides for editing.

Full 20-slide decks at ~3 hours of lecture a week, one chapter per week (a few weeks pair two), plus two optional-chapter weeks before final presentations.

~3 hrs/week · 14 weeks
1

Week 1

Foundations

Lecture 1Introduction to Vibecoding and the AI Ecosystem20 slides · 1 activities
Lecture 2Prompting and Specification Writing20 slides · 1 activities
2

Week 2

Working Inside the Codebase

Lecture 1Agentic IDEs and Vibecoding Workflows20 slides · 1 activities
Lecture 2Giving AI Context20 slides · 1 activities
3

Week 3

Full-Stack Basics

Lecture 1Frontend Vibecoding20 slides · 1 activities
Lecture 2Backends, Databases, and Authentication20 slides · 1 activities
4

Week 4

APIs and External Integrations

LectureAPIs and External Integrations20 slides · 1 activities
5

Week 5

Agents and Automation

LectureAgents and Automation20 slides · 1 activities
6

Week 6

AI Slop and How AI Goes Wrong

LectureAI Slop and How AI Goes Wrong20 slides · 1 activities
7

Week 7

Debugging and Evaluating AI Systems

LectureDebugging and Evaluating AI Systems20 slides · 1 activities
8

Week 8

Multimodal AI

LectureMultimodal AI20 slides · 1 activities
9

Week 9

AI Product Design

LectureAI Product Design20 slides · 1 activities
10

Week 10

Deployment and Operations

LectureDeployment and Operations20 slides · 1 activities
11

Week 11

Security, Ethics, and the Future of AI

LectureSecurity, Ethics, and the Future of AI20 slides · 1 activities
12

Week 12

Optional Chapter A: Building an AI Startup

LecturePricing and Funding an AI Startup13 slides · 2 activities
13

Week 13

Optional Chapter B: AI Slop and Information Pollution

14

Week 14

Final Presentations

No lecture deck this week, reserved for final presentations.

Recommended quiz

Five multiple-choice questions drawn from the core chapters. Click an answer to check yourself, these are also included at the end of the slides PDF.

Q1. In the vibecoding loop (intent, generation, verification, refinement), which two stages belong to the human?

Q2. Why does a human's verification role become MORE important as AI tools gain agency, not less?

Q3. Which tool category lets the model read multiple files, propose multi-file diffs, AND execute commands inside your project?

Q4. A model confidently uses a function from a library version that doesn't exist. What's this an example of?

Q5. Why does the SAME underlying model sometimes feel much smarter in one tool than another?