Ashish Prasad is a Senior Software Engineer Lead (AI/ML) working on large-scale, enterprise AI systems, with a focus on backend architecture, large language models, retrieval systems, and AI reasoning. His work involves building reliable, high-performance, and context-aware AI experiences and integrating advanced foundation models into real-world production environments.
He has contributed to the design of AI agents that can reason over data, execute code, and generate actionable insights, and has experience developing NLP-driven, data-intensive, and mission-critical software across product and R&D teams.
Ashish holds an engineering degree from NITK Surathkal and is deeply interested in applied AI and agentic systems.
Topic- The Anatomy of an AI Agent
Synopsis- Modern AI systems are rapidly evolving from simple prompt-response models to autonomous agents capable of reasoning, using tools, retrieving knowledge, and executing complex workflows. But what actually makes an AI agent work?
Synopsis- Modern AI systems are rapidly evolving from simple prompt-response models to autonomous agents capable of reasoning, using tools, retrieving knowledge, and executing complex workflows. But what actually makes an AI agent work?
In this session, The Anatomy of an AI Agent, we will break down the core building blocks behind modern agentic systems. We will explore how large language models, memory, retrieval, planning, and tool execution come together to create intelligent, reliable, and production-ready AI agents.
The session will focus on practical architecture patterns used in real-world systems, including how agents reason over data, interact with external tools, maintain context, and handle multi-step tasks. Attendees will gain a clear mental model of how AI agents are designed, the trade-offs involved, and what it takes to move from demos to scalable, real-world deployments.
This talk is intended for engineers, architects, and AI practitioners who want to understand how modern AI agents are actually built under the hood.
