Learn Vibe Coding with AI Agents
Build working software by directing AI coding agents instead of typing every line yourself. You will learn how to describe features clearly, review generated code with a critical eye, test it, and keep a project…
Course description
Build working software by directing AI coding agents instead of typing every line yourself. You will learn how to describe features clearly, review generated code with a critical eye, test it, and keep a project maintainable as it grows.
By the end you will have shipped a small product of your own and automated one real workflow, along with a practical sense of where these tools help and where they quietly fail.
Class schedule
- Days & time
- Saturday & Sunday
- Duration
- 8 weeks
What You'll Learn
Skills You'll Gain
Test Yourself
Run your first coding agent
Set up an AI coding tool, ask it to build a tip-splitting calculator, then read every file it created and write one paragraph on how the code works. Most students are surprised how much they can follow.
Hands-on Lab Task
Write a spec that gets it right
Turn a vague request into a spec with context, acceptance criteria and constraints, then run the agent on both versions for the same feature and compare what came back.
Hands-on Lab Task
Build a class attendance app
Scaffold a Next.js-style app with a form, a server route and a database table, then add a monthly attendance summary page through small, separate prompts.
Hands-on Lab Task
Commit, push and deploy
Create a GitHub repository, commit in small named steps, connect a hosting platform, set environment variables and get a live preview URL for every branch.
Hands-on Lab Task
Automate a weekly report with an agent
Build an agent that reads data through an MCP server, drafts a weekly summary and sends it only after a human says yes, with a log of every tool call.
Hands-on Lab Task
Break and fix your own app
Run the testing, debugging and security checklist on your own project. Add tests, reproduce a bug, fix an injection risk and scrub a secret out of Git history.
Hands-on Lab Task
Curriculum
You can't steer a tool you don't understand, and most of the bad outcomes we've seen came from treating the agent as either a genius or an idiot. This weekend explains, in plain language, what a language model actually does, why it sometimes invents things, and how a coding agent wraps a model in a loop with tools so it can read files, write code and run commands.
What we cover
- Tokens, context windows and next-word prediction, without the maths
- Why models hallucinate and how to reduce it with context, examples and verification
- Chat models versus reasoning models versus coding agents
- The agent loop, plan, tool call, observe, repeat, plus permissions and diffs
- Setting up your toolkit, an AI coding agent, an editor, a terminal, GitHub
In the lab
Install and configure an AI coding tool, ask it to build a small tip-splitting calculator page, and trace every tool call the agent made to get there.
Bring back next week
The working calculator and a written account, in your own words, of what the agent did step by step.
Batches
Pick a batch that fits your schedule, then use the enquiry form to reserve your seat.
No open batches right now, submit your details and we'll notify you when the next one starts.
An instructor will be assigned when the next batch is scheduled.
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Requirements
- No coding experience needed. If you can use a browser and install software, you can start.
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