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Impact and Potentials of GenAI to the IT Engineers
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 βBest Practiceβ
- 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 LeftβA 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 β And Iβll 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
Tune in to our latest episode of the LambdaTest Experience (XP) Series featuring πππππ‘π’ππ¬ πππ, Agile Engineering Coach at Raiffeisenbank International AG. In this episode, he sheds light on the impact and potential of GenAI for IT engineers. Discover how GenAI has already revolutionized our world and learn how we leverage it in our enterprise company. Don't miss this insightful discussion.
Video Chapters
00:00 Welcome!
02:26 The Impact of AI on IT Engineers
05:11 Evolution of IT Engineer
10:31 Generating Test Automation Locators
15:50 Generating Code and Deploying Applications
21:36 Use Cases
25:40 QnA
40:51 Conclusion
Key Topics Covered
Introduction and Speaker Background: Introduction to the session and the speaker, Matthias ZAX, Agile Engineering Coach at Raiffeisenbank International AG. Matthias shares his journey from developer to engineering coach, highlighting his passion for software development and test automation.
Impact of Generative AI on IT Engineering: Discussion on how generative AI is transforming the field of IT engineering. Emphasis on the potential of AI to revolutionize code review processes, set up CI/CD pipelines, and translate Behavior Driven Development (BDD) into runnable source code.
Evolution of the IT Engineer : Exploration of the historical evolution of the IT engineering role, from the mainframe era to the current impact of generative AI. Highlighting significant changes brought by technological advancements and the increasing importance of prompt engineering.
Practical Use Cases of Generative AI: Demonstration of how generative AI can generate test automation locators and code, facilitate prototyping, and aid in development tasks. Examples include generating HTML, JavaScript, and CSS from a sketch, and creating shell scripts for deployment.
Best Practices for Integrating AI in Development Workflows: Recommendations for teams to integrate AI into their workflows, including the importance of defining clear prompts, validating AI-generated outputs, and using AI as a co-pilot rather than a replacement. Discussion on the potential pitfalls and the need for human oversight.
Future of AI in IT Engineering: Insights into the future role of AI in IT engineering, with a focus on continuous learning and upskilling in prompt engineering. Emphasis on the quote, "AI won't replace humans, but humans using AI will," underscoring the collaborative potential of AI tools.
Q&A Session : Interactive Q&A session addressing common concerns and strategies for overcoming resistance to AI adoption, achieving faster code feedback, and leveraging AI for test automation and code generation.
Related Blogs & Hubs
Generative AI for Efficient Test Data Generation and Management
Generative AI for Software Productivity: Hype or Hyper Acceleration
Generative AI: A Catalyst for Transformative Automation in Organizations
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