Revolutionizing Development with Gen AI, Automation, and Cloud-Native Approaches

In today's fast-paced digital world, modern development is being transformed like never before. This session explores how the power of Generative AI, Automation, and Cloud-Native architectures is reshaping the way we build, deploy, and scale applications.

We'll look at how Gen AI can boost productivity by helping with code generation, testing, and design ideas. We'll also explore how automation—from CI/CD pipelines to infrastructure as code—helps teams move faster and reduce manual errors. And finally, we'll dive into cloud-native strategies that allow applications to be more resilient, scalable, and cost-effective from day one.

Whether you're a developer, architect, or IT leader, this session will provide practical insights and real-world examples on how to embrace these technologies to build smarter, faster, and more efficient solutions.

Transcript

1. Revolutionizing Development with Gen AI, Automation, and Cloud-Native Approaches
2. 2 about me Asif Waquar Cloud Solution Architect, Munich Re |Singapore asifwaquar asifwaquar https://asifwaquar.com/ @asifwaquar
3. Agenda Understanding Gen AI Shift towards cloud native technologies Low code development Challenges and Key consideration in Emerging Technology
4. Data is more valuable than Oil..
6. Computers have gone smarter… Execute Instructions Learn + Think Gen AI Einstein Asking questions (Prompt Engineering)- Clarity, Simplicity, Context
7. LLM Studio
8. Traditional AI • Machine Learning • Computer Vision e.g. ✓ YouTube recommendations ✓ Web Search Results ✓ Farming ✓ Route map recommendation ✓ Smart Home Generative AI • LLMs (Pre trained Models e.g. ChatGPT) • Natural language communication e.g. Llama 3.2, Mistral, Phi 3.1, Gemma 2, DeepSeek 2.5, Qwen 2.5 Classify existing contents Create new content with LLMs AI in daily life
9. But.. According to a Gartner research, only 15% of AI solutions deployed by 2022 will be successful, let alone create ROI positive value. Why do 87% of the data science projects never make it into production ? Why most AI implementations fail, and what enterprises can do to beat the odds Hundreds of AI tools have been built to catch covid. None of them helped.
10. Why.. Leadership support Vision, strategy and Resources Innovation at scale Data Quality and Accessibility Scattered, Siloed and Messy Lack of Unified Data Platform Governance Standards Collaboration and communication Cross Functional Team Value chain, Experience to science
11. The Evolution is faster than ever..
12. How do we make it real ?
13. How.. • User Centric Analysis • Human Centered Design • Tech Relevance Assessment Understanding Human Needs • Adopt Simplicity to Maximize Value • Intelligent Apps Strategic AI Integration • Experiment with MVP • Test with Human w/context • Iterate Experiment and Improvise
14. Gandalf AI Challenge https://tinyurl.com/hcltech2024
15. A Low-Code Story..
17. Benefit and challenges Easier to maintain and update code Integrated authentication and role-based management Enhanced enterprise monitoring and governance Limited Customization and Flexibility Scalability Issues in handling large amount of data Integration with legacy application, Restricted access to change the platform and Limited control over source code Performance concern
18. What does it mean to be a modern full stack developer?
19. Pro code to Low Code Journey
20. It’s always been about the less- code !
21. Less Code- Smart Code Less code to maintain & patch Reduced framework and breaking changes- end of life components Metadata driven development Build in auth & Role Base Access Management Simplified Deployment & Versioning
22. How low and pro code developers come together ?
23. Accelerated Development Summary
24. Challenges and Key Consideration Understand Understand Business Needs, Criticality, and Impact Consider Consider Business Drivers and Motivation Avoid Avoid Reinventing the Wheel Plan Plan Your Application Modernization Journey Use Use the Right Tools for Technical and Financial Assessments Follow Follow Cloud Adoption and Well- Architected Framework Best Practices Develop Develop an MVP and Iterate
25. Q/A
26. Thank you..