 Hello, I'm Ruchir Puri and I am an IBM Fellow and Chief Scientist of IBM Research. I'm here to answer three questions about AI for code. The issue with legacy code or older code is that as programming languages and preferences evolve, the skill set for legacy programming languages becomes smaller and smaller. Over time this becomes a bottleneck for enterprises that have built significant code base in that language. You are not able to find enough skills to continue to update that mission critical application. In finance for example, COBOL based applications are running multi-trillion dollar transactions on a regular basis. COBOL isn't a bad language per se, they just aren't enough skilled COBOL programmers to introduce new features and offerings. You want to bring the broader application into a modern environment. Whatever is modern today will be legacy tomorrow. Modernization is a manually intensive drawn out process that can take a decade or more and cost up to a billion dollars. To modernize, you need to keep running existing systems with transactional performance, security and resiliency that's expected while updating the underlying language. To do that, you need to understand how to refactor the system into smaller components or microservices and wherever possible move into a modern language. Generative AI can accelerate the transformation and reduce the cost by orders of magnitude. Generative AI is changing the creative process not just for writers and artists but for software developers as well because coding languages evolve, software developers are in constant demand to update applications to meet modern expectations. Coding assistants powered by Generative AI are the answer to today's legacy code issues. It can selectively translate an older coding language to a more modern language while optimizing for a specific use case and building IT automations all in plain English or the language of your choice. It was Mark Anderson who said in 2011, software is eating the world. We can all agree software has eaten the world. Every enterprise is a software enterprise. The demand for software developers is through the roof. There isn't a skills gap so much as an availability gap but AI can now transform how software is developed, generated and tested. I call it software 2.0. Most software so far has been human generated. In this new automation driven era, most code will be machine generated. That has been the goal since the word artificial intelligence was coined for machines to be able to generate code for themselves. My hypothesis is it will be a decade long journey that we are just beginning now. Human language will become the next interface to programming languages. The history of computer science has been all about abstractions. We used to program in a language called assembly which was close to a machine language. From there we went to Fortron, Kobol, Pascal, then programming languages like C++, Java, then scripting languages like Python, JavaScript and Go. The next abstraction will be human language and that will bridge that gap to modernization unleashing this new era of unprecedented productivity with software 2.0.