Building Apps With AI

People who cannot really write code are shipping working software with Cursor, Claude Code, Replit, Lovable and Bolt. This course teaches that skill honestly: what the tools actually do, how to describe what you want, how to read code well enough to trust it, how to recover when the model breaks your app, git and deploying for people who have never done either, what it really costs, the security holes AI code has by default, and the point where you must learn to code properly or stop.

1. 1What these tools actually do8 minThese tools generate plausible code quickly; deciding whether it is correct is still entirely your job.
2. 2Describing what you want8 minDescribe what must be true and what happens when it fails; the happy path writes itself.
3. 3Reading code you did not write9 minRead code to answer one question at a time, and confirm claims by using the app rather than searching the text.
4. 4When the model breaks your app8 minTwo failed fixes means stop, revert to a working state, and reproduce the bug before asking again.
5. 5Save points: git when you have never used it9 minA commit made while the app works is the only thing that makes a bad hour cost an hour.
6. 6Deploying so a stranger can open it8 minProduction differs from your laptop in configuration, case sensitivity and users, so deploy on day two, not week three.
7. 7What it actually costs7 minUsage-based costs need a hard cap at the provider and a per-user limit in your own code, set before launch.
8. 8The security holes AI code has by default10 minBeing logged in is not the same as being allowed; every query must be scoped to the user the session says you are.
9. 9Where you have to learn to code9 minThe limit is not app size or traffic; it is nobody holding an accurate model of how the system works.