MeetupOnline

Oct 8 - MCP, Agents and Skills Meetup Meetup

OCT8
21:30 · Asia / Kolkata

About this event

Join our virtual meetup to hear talks from experts on MCP, agents and skills.

Date, Time and Location

Oct 08, 2026
9:00 AM - 11:00 AM PST
Online. Register for the Zoom!

Designing Multi‑Agent Systems: Sequential, Parallel, and Beyond with ADK

Multi‑agent systems are powerful but choosing the wrong interaction pattern can quickly lead to fragile, slow, or expensive AI systems.
In this talk, we explore the core multi‑agent design patterns enabled by ADK, including sequential, parallel, and more advanced coordination models. Rather than focusing on tools alone, we’ll look at how to think architecturally about agent collaboration.

You’ll learn

When sequential agents are the right choice and when they become a bottleneck
How parallel agents improve speed and coverage (and the trade‑offs they introduce)
Common failure modes in poorly designed agent interactions
Practical criteria for choosing the right pattern based on task, latency, and reliability

By the end of the session, you’ll have a clear mental model for designing multi‑agent systems that are intentional, scalable, and production‑ready.

About the Speaker

Dr Roushanak Rahmat is an Enterprise AI Architect, Google Developer Expert (AI & Cloud), and recognized among the Top 100 Women in Tech (2025). With a PhD in Artificial Intelligence and over 15 years of experience, she specializes in designing and delivering enterprise-scale Generative AI, Agentic AI, and Deep Learning solutions that transform industries including healthcare, finance, energy, and public services.

Privacy by Deployment: Architecting Agent-Driven Localization Workflows for Regulated Environments

Most enterprise AI today is private by promise - a DPA, a SOC 2 report, or a contract clause that says, "we won't train on your data". For a regulated buyer, these are remedies after a breach, not controls that prevent or contain one. For organizations in healthcare, finance, defense, and government, privacy often requires stronger guarantees:

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