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Thu, April 23 at 4:30 PM - 5:00 PM GMT+5:30DeepTech TechLead
Using AI in an enterprise environment can feel like driving a high-performance car with no clear path forward. While AI enables extreme development speed, fragmented architectures, legacy systems, and organisational constraints often limit its real impact. This session examines how to move beyond ad hoc approaches and adopt a more structured way of building AI-driven systems at scale.
The talk introduces five core building blocks for effective AI-native engineering: the Agent, the Model, the Methodology, the Spec, and the Context. Together, these elements provide a framework for orchestrating AI systems in enterprise environments, helping teams move from experimentation to reliable, scalable outcomes.
What You Will Learn
Why enterprise environments limit the effectiveness of AI despite its speed advantages
The five core building blocks for orchestrating AI-native engineering systems
How to move from unstructured development approaches to deliberate, scalable AI system design
Who Should Attend
Software developers
Software architects
Platform engineers
Engineering managers and tech leads
Technology leaders implementing AI at scale
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Sunit has two decades of experience working on large enterprise distributed projects ranging from global solutions to digital modernizations. His focus has been on helping clients define their technology strategy and implement digital platforms with cloud native solutions on ambitious projects.
He is passionate about building modern infrastructure that uses cloud ecosystems and adopts cloud native solutions with the infrastructure-as-code paradigm. He is equally invested in working with clients who adopt modern engineering practices and drive technical excellence. Nowadays, he is focusing on the adoption of AI-driven software development.
He is very involved in open source contribution and has built a tool, Data Anonymization, that helps anonymize production data used for performance testing, security testing, debugging production issues, and development purposes.
