esting traditionally consumes 30–40% of a software budget. GPTySoft reduces this dramatically using Vibe-Coding testing tools. Our QA flow uses AI to read frontend behavior, monitor browser network calls, validate API responses, analyze logs and detect bugs automatically. This eliminates manual repetitive work and ensures higher accuracy.
Using AI-supported Playwright, Cypress and API validators, we can test user journeys, API requests, database responses, performance issues and UX problems at high speed. AI also generates real test cases, mock data, YAML pipeline files, and regression scripts making the testing process systematic and reliable.
This allows startups to ship with confidence, reduce production defects, and maintain consistent product quality even with small teams. GPTySoft’s Vibe-Coding QA approach gives early-stage companies an enterprise-grade testing setup at startup pricing.
AI excels at generating test automation code by leveraging Large Language Models (LLMs) that have a deep understanding of code structure and testing frameworks like Selenium.
- Natural Language Prompts: You can ask Cursor to write a test by describing the steps in plain English (e.g., “Create a Python Selenium script to log in to the OrangeHRM website”). The AI then generates the necessary code, including methods like
driver.find_element(By.NAME, "username"). - Codebase Context: Cursor can read and understand the patterns, Page Object Models (POMs), and existing element locators within your entire project. This allows it to generate new code that aligns with your team’s established standards.
- AI-Based Locators: The search results mention the AI’s ability to generate “AI-Based Locators.” This refers to its intelligence in selecting appropriate Selenium locating strategies (
By.ID,By.NAME,By.XPATH, etc.) based on the standard practices it has learned and the context you provide.
Vibe codeing for APP + Vibe coding for Test Automation + Vibe coding for devops automation = Autonomous Software Delivery System