The AI-Native Software Developer: A Strategic approach
As organizations leverage more and more generative AI to augment the SDLC, the need for strategizing on how this ought to be leveraged, and how to govern the scope of change becomes more and more pertinent.
Enterprises are leaning more and more towards accelerating the SLDC with the support of Generative AI. But this raises several new questions. Are we in a new world where the LLM is the compiler and entire systems will be regenerated for every change? What does one need to think about if that is the case? Is that even sustainable?
On the other hand, if we wish to limit the scope of change—what is that scope? How do we ensure that the blast radius of a change is contained?
This session will attempt to highlight what needs to be thought through as enterprises embark on scaling out Gen AI to assist system development. We will take a journey understanding what makes great systems, how the architectural quanta has a role to play, and what has emphemerality go to do with the conversation.
About Raju Gandhi
Raju is a software craftsman with almost 20 years of hands-on experience scoping, architecting, designing, implementing full stack applications.
He provides a 360 view of the development cycle, is proficient in a variety of programming languages and paradigms, experienced with software development methodologies, as well an expert in infrastructure and tooling.
He has long been in the pursuit of hermeticism across the development stack by championing immutability during development (with languages like Clojure), deployment (leveraging tools like Docker and Kubernetes), and provisioning and configuration via code (toolkits like Ansible, Terraform, Packer, everything-as-code).
Raju is a published author, internationally known public speaker and trainer.
Raju can be found on Twitter as @looselytyped.
In his spare time, you will find Raju reading, playing with technology, or spending time with his wonderful (and significantly better) other half.