SF Bay ACM Chapter

Sat, Nov 15 · 8:30 AM PST

Towards Agentic Intelligence: Architectures for Multi-Agent AI Systems

Valley Research Park , 319 North Bernardo Avenue, Mountain View, CA, US

## Event Logistics

2 DAY EVENT! Saturday 11/15 AND Sunday 11/16 (details below)

Students Register for the class at this Eventbrite Link.
https://www.eventbrite.com/e/towards-agentic-intelligence-architectures-for-multi-agent-ai-systems-tickets-1799266537649?aff=SFbayACMmeetup

Pricing, with discounts that stack
* 10% discount when signing up for both days with one purchase
* 20% early bird discount
* NEW: 50% student/unemployed discount. To get the discount code, email proof of full time enrollment or unemployment to . Use the email subject "ACM multi-agent PDS: discount". There is a limited number.

* 50% BOGO discount. Buy one ticket and sign up two people, for a limited number of tickets. This 50% discount does not include the regular food or drink. This discount stacks with "early bird", "student" or "2 days" discounts.

All pricing includes a $20 annual membership to the SFbayACM

We accept optional donations to our non-profit organization, which is tax deductible. SFbayACM’s Non-Profit Taxpayer ID: 31-0963922
In past years, we have given $3,500 to support STEM education, judging 1,000+ science fair projects at the Synopsis Science Fair, https://science-fair.org/

Day 1, Labs (details below)

• Saturday, Nov 15 8:30am to 5pm
• Sign up for a limited number of seats in person at
• Valley Research Park, 319 North Bernardo Ave, Mountain View, CA.
• Go to the right side of the building, 2nd door
• Coffee breaks and lunch is included in the price
• Zoom for a remote audience
• Both the local and remote audience will be supported by TA’s. The moderator will watch the Zoom chat for questions for the speaker, and ask them.
• Remote tickets have a built in discount, because food is not provided

Day 2, Lectures (outlined below)

• Sunday, Nov 16, 9am to 5pm, only on Zoom
• Zoom for a remote audience
• The remote audience will be supported by questions that can be directed to the speaker by the moderator
• Remote tickets have a built in discount, because food is not provided

## Overview

Building on the tremendous response to Dhanashree Lele’s ACM talk on Multi-Agent Architectures for Enterprise AI, this 2-day, research-caliber, hands-on workshop is designed to advance the state of practice in Agentic AI system design, evaluation, and optimization.
This workshop will guide participants through theory-to-deployment workflows for constructing next-generation multi-agent frameworks, benchmarking agentic behaviors, and applying compute-efficient orchestration strategies. The curriculum draws heavily from recent breakthroughs presented at NeurIPS, ICLR, and KDD, grounding hands-on engineering in rigorous scientific principles and reproducible experimentation.
By bridging academic research and production-grade engineering, this workshop is ideal for applied researchers, industry practitioners, graduate students, and technical leaders seeking to design reliable, interpretable, and high-performance LLM-based agentic systems.

## Learning Format and Structure

This intensive two-day workshop follows a progressive “build-as-you-learn” methodology. Each module introduces core research concepts followed by guided implementation in Jupyter/Google Colab, enabling participants to translate theory directly into working systems.

### 📅 Day 1 — Architecting Multi-Agent Systems

• 4 hands-on labs focused on:
• Building multi-agentic systems/use-cases from first principles
• Exploring agent tools, MCP operability, and orchestration strategies
• Converting agentic prototypes into robust, production-ready cognitive pipelines

### 📅 Day 2 — Deep Dive: Research Frontiers and Reproduction

• Analytical walkthroughs of seminal and frontier papers in Agentic AI from NeurIPS, ICLR, and KDD
• Structured methodology for paper-to-prototype translation: reproducing cutting-edge research through practical labs
• Discussions on evaluation benchmarks, alignment frameworks, and emergent behavior analysis

## Key Outcomes

Theoretical Foundations: Understand the mathematical and algorithmic underpinnings of multi-agent LLM architectures, orchestration, and alignment.
Hands-On Mastery: Gain practical experience in building agentic systems from scratch, configuring MCP operability, and scaling prototypes into production-grade deployments.
**Evaluation & Governance:**Learn to design and apply alignment and evaluation frameworks to ensure robustness, interpretability, and responsible deployment of multi-agent systems.
Practical Assets: Walk away with fully functional notebooks, baseline reference architectures, curated reading lists, and reproducible workflows to accelerate implementation in your own organization.
ACM Certificate for completing the class.

## Prerequisites

• Intermediate to advanced Python programming is nice-to-have. However, if you are a manager, product manager, CTO or other that wants exposure to the technology, you can still get alot out of the class. You can run code in a Jupyter Notebook step by step.
• Familiarity with APIs and Jupyter/Colab environments is helpful.
• Experience with or interest in LLMs (OpenAI API will be used; open-source alternatives such as Claude, Mistral, and Llama 3 will also be discussed)

## Who Should Attend

• AI/ML Engineers, Data Scientists & AI Practitioners designing or deploying LLM applications
• Applied Researchers & Postdocs exploring Agentic AI, neuro-symbolic systems, or autonomous orchestration
• Technical Leaders & Architects integrating multi-agent reasoning in production environments

## Speaker Bio

Dhanashree is a Senior Machine Learning Engineer and AI Researcher with over a decade of experience designing and deploying advanced AI systems at scale. Her expertise spans architecting multi-agent solutions that integrate Large Language Models (LLMs), computer vision pipelines, and structured data to solve complex enterprise challenges across industries including retail, healthcare, and finance.
At Albertsons, Deloitte, and Fractal, Dhanashree has led the development of production-grade AI applications, focusing on optimization, model observability, and responsible AI practices. Her work includes designing scalable inference architectures for LLMs on modern GPU infrastructures, building hybrid pipelines that fuse vision and language models, and engineering systems that balance performance with ethical and regulatory considerations.
She actively collaborates with research institutions like the University of Illinois. Dhanashree actively engages with the research community and frequently speaks on bridging advanced AI research and production systems.
https://www.linkedin.com/in/dhanashreelele/

Dhanashree gave a prior ACM Talk - “Deploying & Scaling LLM in the Enterprise: Architecting Multi-agent AI Systems”

• Meetup Talk Description, Monday, Sept 22, 2025
• Video recording (2h 3m with many questions)

SPONSOR INFORMATION:
From vision to execution, Ccube partners with forward-thinking clients to co-build Apps, Data, and GenAI solutions across industries. Ccube has 10+ service lines, 30+ happy clients, 90% client retention, and saved clients ~50% costs on average.
Ccube has Silicon Valley roots, deep expertise, customer first approach and leverages lean teams for onsite in US and offshore delivery teams in India.
Watch for us also on
https://www.ccube.com/
https://www.linkedin.com/company/ccube-inc/
https://aws.amazon.com/marketplace

As a way to "thank your sponsor", Ccube invites you to share your contact info, and take a brief survey. A summary of the survey results will be shared at the event.

Wed, Nov 19 · 7:00 PM PST

Designing for Scale, Reliability, and Resiliency: Real-World Lessons

Valley Research Park , 319 North Bernardo Avenue, Mountain View, CA, US

Designing for Scale, Reliability, and Resiliency: Real-World Lessons from Building High-Throughput Systems

LOCATION ADDRESS (Hybrid, in person or by zoom, you choose)
Valley Research Park
319 North Bernardo Avenue
Mountain View, CA CA 93043
Don't use the front door. When facing the front door, turn right along the front of the building. Turn left around the building corner. The 2nd door should be open and have a banner and event registration.

If you want to join remotely, you can submit questions via Zoom Q&A. The zoom link:
https://acm-org.zoom.us/j/94270873151?pwd=DFGIb9xhn5GPv8iJD9Bxt1Ya2qJHmN.1
Join via YouTube:
https://youtube.com/live/

AGENDA
6:30 Door opens, food and networking (we invite honor system contributions)
7:00 SFBayACM upcoming events, introduce the speaker
7:15 speaker presentation starts
8:15 - 8:30 finish, depending on Q&A

Join SF Bay ACM Chapter for an insightful discussion on:

Talk Description:
As modern software systems grow in complexity and scale, the demand for architectures that are not just fast—but also reliable, resilient, observable, and auditable—has never been greater. In this talk, we'll dive into practical strategies and real-world patterns for designing and operating large-scale distributed systems.
Topics include:

• Traffic segmentation and routing strategies across multi-cluster environments
• Patterns for achieving high availability and failover across global infrastructure
• Monitoring and observability at scale: what to measure, how to alert
• Auditing for compliance, trust, and debugging
• Common failure modes and how to build for graceful degradation
• Real examples from mission-critical production systems

Attendees will walk away with architectural insights, tools, and mental models to apply to their own systems, whether working in startups or enterprises.

***

Speaker Bio:
I’m a Senior Software Engineer at DoorDash and previously led platform initiatives at Conviva, where I built scalable, fault-tolerant systems handling tens of millions of sessions daily for customers like Disney, HBO, and Sky. My work has spanned everything from routing frameworks and disaster recovery to monitoring pipelines and SLA enforcement. I’m passionate about making infrastructure reliable and maintainable, and I enjoy sharing lessons learned from real-world systems.
https://www.linkedin.com/in/karanluniya

---

Valley Research Park is a coworking research campus of 104,000 square feet hosting 60+ life science and technology companies. VRP has over 100 dry labs, wet labs, and high power labs sized from 125-15,000 square feet. VRP manages all of the traditional office elements: break rooms, conference rooms, outdoor dining spaces, and recreational spaces.

As a plug-and-play lab space, once companies have secured their next milestone and are ready to expand, VRP has 100+ labs ready to expand into.
https://www.valleyresearchpark.com/

Wed, Jan 21, 2026 · 7:00 PM PST

Taming Tech Debt for Platform Reliability

Valley Research Park , 319 North Bernardo Avenue, Mountain View, CA, US

LOCATION ADDRESS (Hybrid, in person or by zoom, you choose)
Valley Research Park
319 North Bernardo Avenue
Mountain View, CA CA 93043
Don't use the front door. When facing the front door, turn right along the front of the building. Turn left around the building corner. The 2nd door should be open and have a banner and event registration.

If you want to join remotely, you can submit questions via Zoom Q&A. The zoom link:
https://acm-org.zoom.us/j
Join via YouTube:
https://youtube.com/live/

AGENDA
6:30 Door opens, food and networking (we invite honor system contributions)
7:00 SFBayACM upcoming events, introduce the speaker
7:15 speaker presentation starts
8:15 - 8:30 finish, depending on Q&A

Join SF Bay ACM Chapter for an insightful discussion on:

Talk Description:

Site Reliability Engineering (SRE) at Google is a job function, mindset, and set of engineering practices focused on ensuring the reliability, scalability, and efficiency of production systems. The term is created in the early 2000s.

This talk aims to reframe the conversation around technical debt. Rather than viewing it as a mere backlog of chores, I will present a methodical framework for identifying and prioritizing it as a strategic opportunity. Drawing from my experiences at various companies, including Google, I will share practical insights on how to transform tech debt from an impedance to a catalyst for organizational velocity. I will also discuss how to apply SRE principles to measure the reliability of infrastructure as we tackle technical debt and will be sharing a few anecdotes and practical methods to address this interesting problem with engineering and automation.

Speaker Bio:
Saurabh Phaltane is a Senior Site Reliability Engineer at Google, where he focuses on designing and optimizing web-scale infrastructures for resilience and high performance. With over a decade of experience in SRE and distributed systems, Saurabh specializes in building reliable systems through robust infrastructure automation, comprehensive observability, and scalable automation. Prior to his work at Google, Saurabh gained valuable experience as an SRE at Okta. He is also a thought leader in SRE and cloud technologies, a mentor for startup entrepreneurs through the Google for Startups program, and a frequent speaker on the topic of foundational thinking for scalable and reliable system infrastructure.

https://www.linkedin.com/in/karanluniya

---

Valley Research Park is a coworking research campus of 104,000 square feet hosting 60+ life science and technology companies. VRP has over 100 dry labs, wet labs, and high power labs sized from 125-15,000 square feet. VRP manages all of the traditional office elements: break rooms, conference rooms, outdoor dining spaces, and recreational spaces.

As a plug-and-play lab space, once companies have secured their next milestone and are ready to expand, VRP has 100+ labs ready to expand into.
https://www.valleyresearchpark.com/