AI-Powered Development With Code Coverage: Faster Code Without Losing Quality

Описание: In this video I demonstrate my real AI-assisted development workflow focused not only on speed, but also on maintaining code quality.

Modern LLMs can generate code incredibly fast, but they also introduce issues like:

dead code
unreachable branches
unnecessary fallbacks
over-defensive programming
overly broad exception handling

To keep control over the codebase while still benefiting from AI speed, I use a workflow based around automated testing and code coverage.

In this demo:

Magento 2 (Luma)
GitHub Copilot
Cypress
PCOV
Istanbul
PhpStorm
Ubuntu
Mark Shust Docker setup

Topics covered:

AI-generated feature implementation
AI-generated E2E tests
TDD vs code-first approach
Refactoring after AI generation
Backend + frontend code coverage
Reviewing coverage reports
Finding dead code and unreachable branches
Why code coverage becomes much more important in the AI era

I also show:

how PCOV is configured instead of Xdebug for performance
how Cypress and Istanbul are integrated
how coverage reports are generated for both PHP and JavaScript
practical examples of reviewing AI-generated code with coverage reports

This workflow is not about “10x developer” hype.
It is about balancing:

development speed
maintainability
long-term code quality

If you use AI during development professionally, I highly recommend adding coverage-based review into your workflow.

Tools & Stack:

Magento 2
Cypress
PCOV
Istanbul
GitHub Copilot
PhpStorm
Ubuntu
Docker

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