AWS re:Invent 2025 - AI-Driven Testing: Scaling Automation with KaneAI and HyperExecute (AIM230)

AI-Driven Testing: Scaling Automation with KaneAI and HyperExecute

Challenges with Current Testing Strategies

• Fragmented oversight and disconnected testing processes leading to blind spots and misalignment
• Inconsistent testing standards causing variability, quality issues, delays, and eroded customer trust
• Brittle and unscalable testing infrastructure that cannot keep up with modern needs and slows innovation

Why Testing is Breaking

• Majority of time spent on fixing broken and flaky tests, test optimization, execution, and debugging rather than test planning and authoring
• Exponential increase in code volume due to AI-driven development requires more comprehensive testing

Lambda Test's Modern Intent-Driven Testing Workflow

• KaneAI can generate relevant test cases from requirements in natural language (e.g. Jira stories, documents, media)
• KaneAI autonomously authors tests leveraging open source frameworks like Selenium, Playwright, and Cypress
• HyperExecute platform executes tests at scale and provides detailed analysis and root cause identification

Key Features and Benefits

1. Intent-Driven Test Case Generation:

   • Accepts requirements in various formats (text, media, Jira)
   • Analyzes context to generate relevant, non-duplicative test cases
   • Allows human review and editing of generated test cases

2. Autonomous Test Authoring:

   • KaneAI agents autonomously author tests in open source frameworks
   • Supports functional, API, accessibility, visual regression, and performance testing

3. Scalable Test Execution:

   • HyperExecute platform executes tests in parallel across cloud infrastructure
   • Provides detailed reports, logs, videos, and root cause analysis for failures
   • Integrates with CI/CD pipelines and allows scheduled test runs

4. Comprehensive Observability:

   • Detailed test reports with pass/fail rates, execution trends, and failure analysis
   • Accessibility testing with WCAG compliance reports
   • Mobile app performance reports including startup times, CPU/memory usage

Business Impact

• Faster time-to-market by automating the entire testing lifecycle from requirements to execution
• Improved quality and reduced technical debt through early issue detection and remediation
• Increased developer productivity by minimizing time spent on test maintenance and debugging

Real-World Examples

• Identified a bug in the Airbnb website where the map was not displayed above the listings as expected
• Provided detailed reports with screenshots, logs, and root cause analysis to quickly resolve the issue

Availability and Integration

• Flexible deployment models on AWS, including availability on the AWS Marketplace
• Seamless integration with Jira and over 100 other tools through extensive plugin ecosystem