Note Important Registration Information This is an invite-only event with limited capacity. To be considered for attendance, please register using the registration link provided in this Meetup description. Submitting an RSVP on Meetup alone will not be considered a valid registration. All registrations will go through a screening process. If your registration is approved, you will receive a confirmation email. Link for registration- https://sahaj.ai/events/agentic-ai-in-production/
About the Event Agentic AI in Production is a one-day conference bringing together practitioners who have built, tested and evolved agentic systems beyond the prototype stage.
Through real-world systems and hard-earned lessons, the sessions explore architecture, multi-agent coordination, reliability, evaluation, memory, observability and performance. The focus is not on what agents could do, but on the decisions, failures and patterns that determine whether they actually work in production.
Sessions Shift-left Considerations in Agentic AI Karthika Vijayan Agentic system design starts with getting the mental model and problem scope right, rather than jumping straight into agents and orchestration. This talk presents a shift-left approach to thinking about agentic systems, with capability, accuracy and consistency, performance, and modularity considered from the outset. The goal is to build the right system for the problem while anticipating the constraints that will shape it as it grows.
Engineering Agents Beyond the Happy Path Shruti Dhavalikar Building an agentic solution for a large enterprise platform comes with a unique requirement: building not one assistant, but a reusable framework that supports multiple use cases. This talk walks through the design and evolution of that system from three angles: performance, configurability and reusability, and robustness. It explores how a working-but-slow orchestrator can be rebuilt, how modularity enables reuse across use cases, and what evaluations can and cannot catch.
My Agents Can’t Agree and Now It’s an Architectural Problem Yahya Poonawala As natural language semantic complexity increases for an application, building reliable agentic systems becomes more challenging. This talk explores the evolution of a digital advertisement campaign planning assistant from a nominal orchestrator-worker system to an NLP-incorporated, consistency-assured multi-agent system.
Lessons from an Agentic AI Raga-Metal Band Sujit Kamthe This talk explores how eleven specialist agents collaborated to compose raga-metal fusion music using advanced agentic patterns for coordination, critique, and verification. Through shared-blackboard collaboration, evaluator-optimizer loops, deterministic verification, LLM-as-a-judge, and bounded multi-agent debate, the talk examines what belongs in code, what requires model judgement, and how agents should be decomposed around decisions.
Who Watches the Agent? Engineering Trust into Autonomous AI Suman Paul Choudhury Building an AI agent is easy. Trusting one in production is not. This talk explores the harness needed to bridge that gap, from evaluating multi-step agent behavior and enforcing guardrails to making agents observable, debuggable, and reliable. Drawing on the latest research in agent reliability, it looks at practical systems and techniques for turning autonomous agents from unpredictable prototypes into trustworthy production systems.
Lightning Talk: Principles & Strategies for Agent Memory Amit Bhagat Building a basic agent is easy; giving it reliable memory is hard. As interactions grow, naive state management can lead to surging token costs, latency spikes, and context blindness. This talk focuses on the principles of agent state and memory management, and evaluates different strategies for building reliable agent memory.
Lightning Talk: How Hidden Prompt Breaks Production LLMs Vinayak Kadam When LLM-powered applications break in production, engineering teams usually audit system prompts or blame upstream model updates. But system prompts are only half the instruction. Dynamic annotations, schema descriptions, and few-shot payloads injected at runtime can carry equal weight. This talk uncovers hidden failure modes in data-prompt coupling, examines common anti-patterns, and covers practical strategies to retain alignment.
Meet our Speakers Karthika Vijayan Solution Consultant Karthika Vijayan has been conducting research in the field of conversational AI with voice and text data for almost a decade. Her research has been published in several journals and presented at various international conferences. Prior to joining Sahaj, Dr. Vijayan worked as a research fellow in the Department of Electrical and Computer Engineering at the National University of Singapore. She also worked as research associate in the Department of Electrical Engineering at the Indian Institute of Science, Bangalore. She obtained her PhD in Speech Signal Processing from the Department of Electrical Engineering at the Indian Institute of Technology Hyderabad in 2016. She is an active member of IEEE, ACM and APSIPA.
Shruti Prasanna Dhavalikar Solution Consultant Shruti Dhavalikar is a skilled Data Scientist with over 7+ years of experience in the field. With a deep passion for data science and a strong understanding of data patterns, she successfully delivers end-to-end product cycles as well as actively contributes to research projects. She has published and presented research works at several international conferences.
Yahya Poonawala Solution Consultant Yahya Poonawala is a technology professional with over 13 years of experience in software engineering, architecture and engineering leadership. Having worked across product and services organisations, Yahya brings a problem-driven approach to system design, with a keen interest in building scalable, reliable and reusable software systems. His current work at Sahaj focuses on applying these principles to complex engineering challenges, including agentic AI systems.
Sujit Kamthe Solution Consultant Sujit is an engineering leader, software architect and AI practitioner with more than 16 years of experience building distributed systems, cloud platforms and enterprise applications, and building high performing engineering teams. His current work focuses on production-grade agentic AI, cloud-native architecture and AI-assisted software engineering. He writes and speaks about software architecture, engineering practices, developer productivity and the changing role of engineers.
Suman Paul Choudhury Solution Consultant Suman Paul Choudhury is a Data Science Consultant at Sahaj with over 10+ years of industry experience in AI and Machine Learning. His work spans Generative AI, Computer Vision, AdTech, customer analytics and large scale ML systems.Suman has extensive experience working with technologies such as PySpark, deep learning, graph based machine learning, LLMs, LangGraph and modern MLOps ecosystems.He holds a Master’s degree in Signal Processing, has contributed to IEEE research publications and has patent involving vision assisted checkout systems.Suman is particularly passionate about translating complex AI concepts into practical systems that solve real business problems and about helping teams move from AI experimentation to scalable, production ready solutions.
Amit Bhagat Solution Consultant Software Engineer at Sahaj with experience spanning high-throughput telemetry platforms, agentic AI systems, and distributed data engineering. Brings a strong foundation in building resilient backend systems, real-time event-streaming architectures, and cloud infrastructure.
Vinayak Kadam Solution Consultant Vinayak Kadam is a Solution Consultant at Sahaj Software, where he works on AI-powered and multi-agent systems. With experience spanning data engineering, cloud platforms, and large-scale distributed systems, he focuses on building production-ready solutions that combine intelligent automation with practical business outcomes.
Agenda 9:00 AM – 9:30 AM Registration and Networking
9:30 AM – 9:40 AM Introduction
9:40 AM – 10:20 AM Shift-left Considerations in Agentic AI Karthika Vijayan
10:25 AM – 11:05 AM Engineering Agents Beyond the Happy Path Shruti Dhavalikar
11:05 AM – 11:20 AM Break
11:25 AM – 12:10 PM My Agents Can’t Agree and Now It’s an Architectural Problem Yahya Poonawala
12:15 PM – 1:00 PM Lessons from an Agentic AI Raga-Metal Band Sujit Kamthe
1:00 PM – 2:00 PM Lunch Break
2:05 PM – 2:45 PM Who Watches the Agent? Engineering Trust into Autonomous AI Suman Paul Choudhury
3:35 PM – 3:50 PM Lightning Talk: Principles & Strategies for Agent Memory Amit Bhagat
3:55 PM – 4:10 PM Lightning Talk: How Hidden Prompt Breaks Production LLMs Vinayak Kadam
4:10 PM – 4:25 PM Break
4:25 PM – 5:30 PM Birds Of A Feather / Open Discussion
