Amikoo Blog

You can configure agents to watch your repository, read the diff on every pull request, find the coverage gaps the change introduced, and commit the missing Playwright tests to that PR before a human reviews it. In this live demo, MuukLabs CTO Renan Ugalde shipped two features — a login redesign and a new dashboard — without hand-writing a single test, then used a second agent to separate real defects from environment noise in the failures.

You connect an AI tool to your repository; it reads the codebase to map out real user journeys (login, checkout, navigation, etc.), then generates a full Playwright test suite — selectors, assertions, and all — for you to review and run. Below is exactly how that process works with Amikoo our AI QA tool, what to check before trusting the output, and where it fits if you already know Playwright.

General-purpose LLMs and coding agents like Claude Code handle your first 20–50 end-to-end test cases well. As your application grows more complex and your suite grows into the hundreds, three problems emerge: poor context management (which can burn 20x more tokens than necessary), test drift (tests that quietly "fix" themselves into false positives), and multi-agent communication failures. Each has a concrete fix, covered below. That was the core of this Amikoo webinar, where MuukLabs CTO and co-founder Renan Ugalde, hosted by CEO and co-founder Ivan Barajas, dug into what teams actually experience when they use LLMs for end-to-end test automation. Writing test scripts is no longer the hard part; the challenge has shifted to managing context, drift, and agent coordination at scale.

Federal Award Validates Amikoo, MuukLabs’ Agentic AI Solution for Modern QA Bottlenecks

Launch signals the death of no-code test automation, giving QA teams up to 8x more capacity overnight to "fight fire with fire" alongside AI-accelerated developer teams.