Task

The Image Gen Extension addresses a practical task: a browser extension for generating images within an editor context. TypeScript MV3 and UX for prompts and previews.

This is a personal learning project (currently in development) where specific patterns and tools were practiced without unnecessary overhead.

The case study demonstrates an approach to tasks in the field of "Implementing Artificial Intelligence": from problem definition to delivery with a clear module structure.

Before starting, we established readiness criteria: a clear first screen, predictable form errors, and the ability to make improvements without rewriting half of the codebase.

Solution

A learning but fully functional implementation has been made with an emphasis on code readability and reproducible builds.

The scenarios are designed so that the main actions fit within one or two screens: fewer switches, fewer input errors. Navigation and field labels are aligned with familiar patterns — the user does not need to "learn the interface".

Particular attention is paid to loading states and empty lists: skeleton/spinner where data comes asynchronously, and clear empty-state texts instead of an empty table.

Architecture and stack

Infrastructure and utilities: TypeScript, WebExtension, Chrome.

Language distribution in the repository: JavaScript (89%), CSS (11%).

Layers are separated so that the UI does not know the details of transport: API/storage adapters, domain types, presentation components. This simplifies backend replacement and targeted UX adjustments.

Key features

• TypeScript — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• WebExtension — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.
• Chrome — used in product logic: reduces the amount of custom code and speeds up the addition of new screens.

Additionally:

• Integration and use of TypeScript in product logic and interface.
• Integration and use of WebExtension in product logic and interface.
• Integration and use of Chrome in product logic and interface.

Result

The MVP already covers the key scenario; next — expanding reporting, tests, and monitoring.

The source code is open: https://github.com/astropsy999/image-gen-extension — you can evaluate the module structure and commit style.

What I would improve

The next step is observability (logs/metrics), regression auto-tests, and API documentation for integrators. For high-load scenarios — profiling bottlenecks and caching reference data.