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AARRR...Are you Test-Ready for AI? Discover If AI Can Transform QA Process
AARRR...Are you Test-Ready for AI? Discover If AI Can Transform QA Process
Playlist
- Client Feedback & Quality Assurance in Web Design for Agencies
- Democratise Automation to Build Autonomy and Go-To-Market Faster
- Testing AWS applications locally and on CI with LocalStack
- Man Vs Machine: Finding (replicable) bugs post-release
- Shift-Left: Accelerating Quality Assurance in Agile Environments
- End-to-End Test Automation with Provar
- Fast-Tracking Project Delivery:Tips from a Recovering Perfectionist
- Crawl, Walk, Run...Fly - Take your build and test pipeline to the next level
- Revolutionizing Testing with Test Automation as a Service (TaaS)
- How Codemagic Mitigates Challenging Mobile App Testing Environments
- Fast and Furious: The Psychology of Web Performance
- Faster Feedback with Intelligent CD Pipelines
- Navigating the Future of Quality Engineering in 2024
- Using AI for Effective Test Generation
- Automated Test Execution Reporting
- How To Speed Up Our Work During Web Automation
- Building Products that Drive Better Results with Shortcut
- Shifting Accessibility Testing Left with LambdaTest and Evinced
- Testing Tomorrow: Unravelling the AI in QA Beyond Automation
- Flaky Tests from an Engineering Perspective
- Future Trends and Innovations in Gen AI for Quality Engineering
- Mastering User-Centric Mindset Unlocking Your Potential as a Tester
- From Brainwave to Inbox: Avo's Whimsical Adventure through AI-Powered Test Automation
- The Myth of โBest Practiceโ
- Impact and Potentials of GenAI to the IT Engineers
- Innovation Accelerated: The Intersection of AI and Quality Engineering
- Optimize Issue Tracking: Integrating SpiraTeam with LambdaTest
- The Power of Generative AI in Reducing Maintenance and Enhancing Speed
- Rethinking the Role of QA Profile
- Building Quality Software: AI-based testing approach with Jira and QMetry
- In-Depth with Playwright: A Modern Testing Framework
- Supercharge Your Data Quality Testing with AI/ML
- GenAI for Quality Transformation
- Creating Reliable and Scalable Test Automation Frameworks
- Upskilling Quality Engineers: A Success Story in SDET Transformation
- AI-Readiness: Are You Building the Future or Falling Behind
- Leading the Charge in Software Quality with Zero Bug Revolution
- Building a Test Automation Framework for TV Apps & Scaling at FX Digital
- Building High-Quality Teams: People, Process & Proof for QA Leadership
- Why Do We Have Bugs, and Why Do They Happen?
- GenAI in QA: Tiket's Approach to Evolving Quality Engineering
- Collaborative Remote Testing: How to Set Up & Run Effective Ensemble Sessions
- Simulating Real-World Scenarios: Balancing Precision and Practicality in Testing
- Building AI-Driven Test Automation Frameworks for QA Excellence : Challenges with Agile, DevOps, and AI-driven Testing
- Reinforcing Cybersecurity Beyond Functional Testing
- Building AI-Driven Test Automation Frameworks for QA Excellence
- Shift Happens: Driving Quality LeftโA Real-World Journey Across Five Teams
- Transitioning from Manual Testing to Test Automation with Cypress
- See Why Your Testing Framework Is Incorrect, Incomplete, or Inefficient โ And Iโll Show You Why
- Quality First: Implementing Shift-Left Testing for Future-Ready Products
- Building Resilient Quality Engineering Teams: Exploring Emerging Trends and Best Practices
- Testing LLMs: Why It Matters, Common Data Challenges, and Proven Testing Strategies
- Observability in Software Test Modernization
- AARRR...Are you Test-Ready for AI? Discover If AI Can Transform QA Process
- Integrating Testing into Agile Workflows: Enabling Faster, Smarter Software Delivery
About The Video
In this XP Series episode, ๐๐ฎ๐๐ฒ ๐๐ฎ๐ฌ๐ฅ๐จ๐ฏ๐, Head of Quality Engineering Excellence at Intellias, explores a critical question: Do you really need AI in your QA process?
Using the AARRR framework, Lucy unpacks how to evaluate the real impact of AI on:
โ Test automation effectiveness
โ Engineering productivity
โ Team collaboration across QA
Video Chapters
00:00 Welcome
01:14 Guest Introduction
03:59 Understanding the AARRR Framework
13:15 Key Organizational Challenges in AI Implementation
17:23 Maturity Assessment for AI Adoption
20:52 Self-Healing Tests and AI Integration
27:12 Guardrails for AI Usage in QA
33:01 Transforming the Role of QA Engineers
39:40 Wrapping Up
Key Topics Covered
Understanding the AARRR Framework: An overview of the AARRR model, which stands for Acquisition, Activation, Retention, Referral, and Revenue, and its relevance in evaluating AI systems.
**Assessing AI Readiness: Discussion on how organizations can determine if they are prepared to integrate and scale AI technologies effectively.
AI Testing Strategies: Insights into methodologies and best practices for testing AI models to ensure reliability and performance.
Challenges in AI Implementation: Identification of common obstacles faced during the adoption and testing of AI solutions.
Related Blogs & Hubs
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