Applied AI Building
Use AI coding assistants to specify, build, test and improve practical digital tools.
Open any lesson to see its learning objective. The lesson activities are being prepared.
Plan the Product
Choose a Real Problem and User
Describe the target user and a narrowly scoped need.
Write a Build Specification for Codex
Convert the need into concrete functionality and constraints.
User Journeys, Screens and Data Flow
Plan interactions and how information moves across the product.
Acceptance Criteria and Risk Boundaries
Define verifiable completion conditions and security constraints.
Build with AI Assistance
Prompting Codex for Small, Reviewable Steps
Break implementation into testable tasks rather than one giant request.
Files, Git and Safe Checkpoints
Understand project structure, version changes and how to revert.
Frontend, Local Data and Interactive Simulations
Create a browser-based prototype that works without live APIs.
Mock Integrations and Data Contracts
Simulate realistic requests, responses and failure states.
Test, Release and Demonstrate
Functional Tests and Acceptance Checks
Verify that requirements are met on supported devices.
Security and Privacy Review of the Prototype
Check data exposure, inputs, permissions and honest claims.
Debugging, Deployment and Release Checklist
Fix issues, run QA and prepare a stable public demonstration.
Document Results and Plan Improvements
Write a portfolio case study including limitations and next steps.