Kalaranjani

Software architecture has continuously evolved—from monolithic applications to distributed systems, cloud-native architectures, microservices, and now intelligent and agentic systems. While many foundational architectural principles remain relevant, AI introduces a fundamentally different class of components into enterprise solutions: components capable of reasoning, making decisions, using tools, maintaining context, and collaborating with other agents.

What does this mean for the software architect?

This session explores the changing responsibilities of architects as enterprise applications move from predominantly deterministic workflows toward systems that combine conventional software components with AI models and autonomous or semi-autonomous agents.

Drawing on practical enterprise architecture and emerging agentic solution-design experience, the session examines how architects need to rethink system boundaries, agent responsibilities, orchestration, context and memory, integration patterns, observability, governance, security, and human oversight. It will also explore how AI is changing the architect’s own workflow by assisting with requirements analysis, solution exploration, documentation, implementation, and architectural decision-making.

The session presents intelligent-system architecture not as a replacement for traditional software architecture, but as its next evolution—requiring architects to combine established engineering discipline with new patterns for designing systems whose behavior is increasingly dynamic, contextual, and intelligent.

Biography:

Kalaranjani Sathishkumar is a Senior Solutions Architect and IEEE Senior Member with more than 17 years of experience in enterprise software engineering, solution architecture, and technology delivery. She specializes in translating complex business needs into scalable enterprise architectures, with experience spanning cloud platforms, distributed applications, system integration, application modernization, architecture governance, and large-scale technology delivery.

Her recent work focuses on AI and agentic solution architecture, including the design of enterprise systems in which AI agents orchestrate workflows, interact with enterprise services and data, and collaborate to perform complex tasks. She has also worked on applying AI-assisted approaches across the software development lifecycle, including requirements analysis, architecture documentation, development support, and test-data generation.

Her professional interests center on the evolution of software architecture as AI becomes a first-class component of enterprise systems—particularly the architectural implications of agent orchestration, system boundaries, context and data management, observability, governance, security, and human oversight.