AI-assisted development process
IoT Digital Platforms
Use AI development tools in a controlled way for coding support, test ideas, documentation drafts, and repeatable prompts.
What this bullet means
The employer wants AI curiosity plus discipline: prompts, outputs, review notes, and final code decisions should be documented instead of treated like magic.
Sample app idea
AI-Assisted Development Log that stores prompt goals, generated suggestions, review decisions, tests run, and final implementation notes.
Main build outline
- Create records for prompt goal, context provided, AI suggestion, developer review, and final decision.
- Add categories for coding, testing, documentation, refactoring, and troubleshooting prompts.
- Require a human-review status before any AI suggestion is marked accepted.
- Add a small prompt library with reusable prompts for tests, documentation, and code review preparation.
- Document AI usage boundaries, verification steps, and secret-safety rules.
Portfolio proof
- AI development log screenshot with prompt, suggestion, review, and final decision fields.
- Prompt library README showing repeatable prompts for coding, testing, and documentation.
- Verification note showing tests or manual checks after AI-assisted work.
Minimal documentation
- README with the business problem, screenshots, setup notes, and technology stack.
- One requirements note that maps the job bullet to the sample feature.
- One test plan note with happy path, validation, and edge case checks.
- One honest portfolio note that says this is self-directed practice, not employer work.
Modern .NET stack
- Blazor Server or ASP.NET Core Razor Pages.
- C# services with validation and dependency injection.
- SQL Server locally, then SmarterASP SQL Server or Azure SQL.
- Optional Azure App Service, GitHub Actions, Docker, and AI helper feature.