30+

Expert Instructors

50+

Workshops & Demos

1k+

Builders, Engineers, & Innovators

$2,500

AI Platform Credits

Preliminary Schedule Overview

All sessions are scheduled in Eastern Time (ET), beginning at 12:00 PM and concluding around 5:30 PM ( 9:00 AM–2:00 PM Pacific Time (PT)

Week 0 - Introductory Workshops

Theme: Build Your First Agent – Tools, Prompts, and Use Cases

1. The A to Z of Building AI Agents

Speaker: Apoorva Joshi‍

2. The Age of AI Agents and Product Development

Speaker: Martin Musiol

3. From Concept to Creation: Building Advanced AI Applications with LLM’s and AI Agents

Speakers:
Atul Kulkarni
Lakshmithejaswi Narasannagari

4. Introduction to Retrieval-Augmented Generation (RAG)

Speaker: Sheamus McGovern

5. Building with MCP: Model Context Protocol for Multi-Agent Systems

Speaker: Sheamus McGovern

6. Building AI Agent Workflows: Automating Research Papers to Podcasts

Speaker: Tony Kipkemboi

7. Building AI Evaluations: DeepSeek vs OpenAI in action

Speaker: Raza Habib

8. Build a Data Analyst AI Agent from Scratch

Speaker: Daniel Herrera

Week 1 - Foundation

Theme: Understanding AI Agents and Their Business Impact

Jan 21st, 12:00 PM -12:30 PM , ET

Business Talk: Getting Started with Agentic AI in the Enterprise

Dr. Ali Arsanjani - Director of Applied AI Engineering | Head of AI Center of Excellence | Google Cloud

Jan 21st, 12:35 PM - 1:35 PM , ET

Prompt Engineering for Coding Agents: From First Prompt to Production Workflows

Karen Zhou - Member of Technical Staff | Anthropic

Coding agents are transforming how developers build software, but getting consistent, high-quality results requires understanding how to communicate effectively with these systems. This hands-on workshop teaches prompt engineering techniques specifically optimized for agentic coding workflows, drawing from real patterns used by engineers at Anthropic building and deploying Claude Code.
Attendees will learn why prompting for agents differs fundamentally from prompting for chat-based interactions. Agents operate in loops—perceiving their environment, reasoning about next steps, taking actions, and incorporating feedback—which means prompts must guide behavior across multiple turns rather than elicit a single response. We'll cover techniques like structuring context with CLAUDE.md files, triggering extended thinking modes (""think"" → ""ultrathink""), designing effective test-driven development workflows, and managing context across long-running sessions.
The workshop targets software engineers, ML engineers, and technical leads who want to integrate coding agents into their development workflows. Whether you're building internal tools, shipping production applications, or exploring agentic architectures for your organization, you'll leave with practical skills you can apply immediately.
Key learning outcomes include understanding the agent loop (perception → reasoning → action → feedback), writing prompts that guide multi-step coding tasks, configuring project-level context and memory, implementing workflows with agents, and debugging common failure patterns like context loss and over-engineering. Participants will work through exercises using Claude Code and the Claude Agent SDK, building progressively complex workflows from simple code generation to multi-agent architectures.

Jan 21st, 1:40 PM -2:40 PM, ET

From RAG to AI Agents

Sara Zanzottera - Agentic AI Lead | BGB Group

As the capabilities of modern LLMs grow, their fields of application also widen. In order to meet the expectations of your customer, a simple RAG application is not sufficient anymore: they expect the chatbots to use tools, to search the web, to self correct, and more. In short, they want an AI Agent.
In this workshop we're going to explore how to take your existing RAG pipeline and, step-by-step, transform it into an agentic system, without throwing away all the work your team has done so far. We will first create a very small RAG application and then upgrade the system, one step at a time, until we have a fully-fledged agent that can take on long running tasks.
This workshop is not tied to any specific framework: we will work from first principles and cover the concepts as well as the implementations, so that you can apply these concepts to your specific infrastructure and tools.

Jan 21st, 2:45 PM - 3:45 PM, ET

Memory for AI Agents

Vasilije Markovic - CEO | cognee

Connecting your company data to LLMs might seem easy—until you try to do it quickly, and at scale.
With large volumes of data, challenges like data consistency, data contracts, modularity, and developer experience rise up. You might end up with a lot of microservices and very fragile systems.
We will discuss how we designed cognee, a scalable AI Memory Python SDK that supports multiple Graph and Vector databases and integrates with various LLMs. We will also look into how cognee works using an example of connecting unstructured and structured finance data.
Based on a real-word example from the finance domain, you'll learn what AI memory is and how to give your LLMs the context they need.

Jan 21st, 3:50 PM - 4:50 PM, ET

Developing a Tool Calling Agent from Scratch

Misam Abbas- Staff AI Engineer | LinkedIn

Jan 22nd, 12:35 PM - 1:35 PM, ET

Building Scalable AI Agents with Ray, LangGraph and Strands Agents

Suman Debnath- Technical Lead (ML) | Anyscale

Jan 22nd, 1:40 PM - 2:40 PM, ET

Popular AI Agent Frameworks

Sydney Runkle - Software Engineer | LangChain

Jan 22nd, 2:45 PM -3:15 PM, ET

Business Talk: Governance of AI and Agentic Systems

Paul Dongha - Head of Responsible AI & AI Strategy | NatWest Group

Week 2 - Implementation

Theme: Advanced Patterns and Industry Solutions

Jan 28th, 12:00 PM -12:30 PM, ET

Business talk : Designing Agentic Workflows for Operational Efficiency

Dr. Ali Arsanjani - Director of Applied AI Engineering | Head of AI Center of Excellence | Google Cloud

Jan 28th, 12:35 PM - 1:05 PM, ET

Business talk : AI Agents in Operations

Cameron Royce Turner - Founder and CEO | TRUIFY.AI

Jan 28th, 1:10 PM -2:10 PM, ET
What’s your Agent's GPA? A Framework for Evaluating AI Agent Reliability

Josh Reini - Developer Advocate | Snowflake

Agents often fail in ways you can’t see. They could return a final answer while taking a broken path: drifting from the goal, making irrational plan jumps, or misusing tools. Was the goal achieved efficiently? Did the plan make sense? Were the right tools used? Did the agent follow through?
These hidden mistakes silently rack up compute costs, spike latency, and cause brittle behavior that collapses in production. Traditional evals won’t flag any of it because they only check the output, not the decisions that produced it.
This session introduces the Agent GPA (Goal-Plan-Action) framework, available in the open-source TruLens library. Benchmark tests show the Agent GPA framework consistently outperformed standard LLM evaluators, giving teams scalable and trustworthy insight into agent behavior.
95% error detection (vs. 55% baseline methods)
86% accuracy in pinpointing where an error occurred (vs. 49% baseline methods)
Across all error severities, matched 100% of human-labeled failures from TRAIL/GAIA dataset
You’ll learn how to inspect an agent’s reasoning steps, detect issues like hallucinations, bad tool calls, and missed actions, and leave knowing how to make your agent truly production-ready.

Jan 28th, 2:15 PM - 3:15 PM, ET

Building a code QA Agent with CrewAI

João (Joe) Moura - CEO | CrewAI

In this workshop, you’ll learn how to build a simple Crew that can review your code, flag potential issues, and recommend improvements to boost overall quality. We’ll start with a 15-minute overview of Crew concepts and a quick setup walkthrough. Then we’ll spend the next 40 minutes hands-on, building a QA assistant you can adapt and use in your own day-to-day development workflow. By the end, you’ll leave with a working foundation and clear next steps for extending it to your projects.

Jan 28th, 3:20 PM - 4:20 PM, ET

Agent2Agent (A2A) protocol

Holt Skinner - Developer Advocate | Google Cloud AI

This course provides a practical introduction to the Agent2Agent (A2A) protocol. You'll learn how to build AI agents that can discover, communicate, and collaborate with other agents, regardless of their underlying framework. This course is for individuals familiar with Gen AI concepts.

Jan 28th, 4:25 PM - 5:25 PM, ET

From Intelligent to Agentic Applications: Using Model Context Protocol to Support Agentic Behaviors in your Applications

Kyle Stratis - Founder | Stratis Data Labs

Jan 29th, 12:00 PM -12:30 PM, ET

Business Talk: Governing Data in the Agent Era: Redesigning Teams, Roles, and Accountability for AI That Acts

Srikanth Thiagarajan - Head of Data office | Marvell Technology

Manoj Saxena - Founder & CEO | Trustwise

Jan 29th, 12:35 PM - 1:05 PM, ET

Business Talk on agent supervision

Matan-Paul Shetrit - Director of Product , a leader and pioneer in enterprise AI | Writer

5. Visual Agents: What it Takes to Build an Agent that can Navigate GUIs like Humans

Harpreet Sahota - Hacker-in-Residence | Voxel51

Jan 29th, 1:10 PM -3:10 PM, ET

Visual Agents: What it Takes to Build an Agent that can Navigate GUIs like Humans

Harpreet Sahota - Hacker-in-Residence | Voxel51

This workshop provides a comprehensive, hands-on introduction to building GUI agents—AI systems that can understand and interact with graphical user interfaces. Participants will begin by exploring the landscape of GUI agent research, understanding why standard computer vision approaches fail on interface tasks and examining influential datasets and models that have shaped the field. The workshop then transitions to practical dataset creation, where attendees will build production-ready GUI datasets using FiftyOne, learning specialized annotation strategies and techniques for scaling data collection. Finally, participants will fine-tune foundation models like Qwen2.5-VL into GUI specialists, implementing training pipelines that handle coordinate prediction and multi-step reasoning. By the end, attendees will have both theoretical understanding and practical skills to contribute to the rapidly evolving field of GUI automation, including a complete dataset and a trained model ready for real-world deployment.

5. Know Before You Deploy: 10 Learnings After a Year of Agentic AI Development

Shane Murray, Field CTO & Head of AI Strategy | Monte Carlo
‍
Nearly every data organization is under pressure to deploy Agentic AI initiatives, but where do they start? What do data teams actually need to know before they begin?

Join Shane Murray, Field CTO & Head of AI at Monte Carlo, as he shares the takeaways his team has learned in the Agentic AI development process. Attendees will walk away with a deeper understanding of best practices for Agentic AI product research, validations, task splitting, workflows, security, and perhaps the most difficult, knowing when to be patient.

Jan 29th, 3:15 PM - 5:15 PM, ET

Hands-On Training on Agent Evaluation and API Integration

Zain Hasan, PhD - Staff AI/ML Engineer - DevRel | Together AI

Week 3 - Scale

Theme: Production Deployment and Business Transformation

Feb 4th, 12:00 PM -12:30 PM, ET

Fireside Chat with US Bank SVP and Head of AI: Measuring ROI and Impact When AI Becomes Digital Labor

Manoj Saxena - Founder & CEO | Trustwise
Sammy Assefa - Senior VP, Head of AI | U.S. Bank

Feb 4th, 12:35 PM - 1:35 PM, ET

Session by Qdrant Coming Soon

Feb 4th, 1:40 PM -2:40 PM, ET

AI Agents on Autopilot

Claire Longo - AI Researcher | Comet

AI Agents promise massive efficiency gains, but building them to take optimal actions and continuously improve over time is still extremely difficult. Many Agent systems today remain surprisingly static. Their behavior is often bottlenecked by brittle, manually written prompts created through trial-and-error, making them fragile and difficult to generalize to real-world data. As LLMs evolve into multi-step Agents equipped with tools, memory, and retrieval, the real challenge is no longer creative prompt engineering, it’s context management and automated optimization.
This workshop teaches you how to build AI Agents that can optimize themselves. You’ll implement a lightweight Agent and integrate automatic Prompt Optimization using the Opik Agent Optimizer SDK. We’ll discuss and compare optimization strategies from GEPA to the new Hierarchical Adaptive Prompt Optimizer (HAPO) to show how these algorithms can balance latency, cost, and accuracy.
By the end, you’ll understand why the future of Agentic AI isn’t about writing better prompts, it’s about designing optimization loops and collecting high-quality feedback datasets. You’ll see how leading AI teams can build self-improving Agents and how you can adopt these techniques in your own work today with completely open-source tools.

Feb 4th, 2:45 PM - 3:45 PM, ET

Real-Time Agents & Live Context Pipelines

Feb 5th, 12:00 PM -12:30 PM, ET

Business Talk : The End of SaaS as You Know It: Niche Agents, Workflow Capital, and the Death of the UI

Ivan Lee - CEO | Datasaur

For 20 years, SaaS was simple: build once, sell 10,000 times, and scale to $100M+ on the back of a generic product and a slick UI. AI agents quietly break that model.
In an agent-native world, the real IP isn’t the app—it’s your workflows. The most valuable agents will be deeply wired into an individual organization’s data, permissions, edge cases, and “unwritten rules.” That means every serious deployment becomes bespoke: custom integrations, domain-specific behavior, and guardrails that map to your risk posture. And if an agent genuinely captures your secret sauce, you’re not going to let a vendor productize it and sell it to your competitors.

This session will cover:

Why “one-size-fits-most” SaaS UIs give way to invisible, workflow-native agents

How agent customization, not features, becomes the core value driver

What this shift means for software buyers (owning your workflows) and vendors (moving from products to primitives, platforms, and services)

Strategic implications for valuation, defensibility, and GTM in a world where no two agents look the same

If your roadmap still assumes classic SaaS economics, you’re already behind.

Feb 5th, 12:35 PM - 1:35 PM, ET

From Agents to ROI: Building Agentic AI Systems That Actually Deliver Value

Sinan Ozdemir - AI Author and Educator

The hype cycle around AI agents has reached a fever pitch but the gap between impressive demos and measurable business outcomes remains wide. In this hands-on workshop, we cut through the noise to focus on what actually matters: building agentic AI systems that deliver quantifiable ROI.

We'll start by establishing a practical framework for evaluating where agents make sense versus where simpler solutions win. Not every workflow benefits from autonomy, and understanding this distinction is the difference between a successful deployment and an expensive experiment. From there, we'll dive into the architecture of production-ready agent systems covering tool selection, memory design, and the critical decision points that determine whether your agent becomes a reliable collaborator or an unpredictable liability.

Through live code walkthroughs and case studies drawn from real enterprise deployments, you'll see how to measure agent performance beyond accuracy: latency, cost-per-task, error recovery rates, and the metrics that actually correlate with business value. We'll tackle the hard problems: hallucination mitigation, graceful failure modes, and human-in-the-loop design patterns that keep agents useful without requiring constant supervision.
Attendees will leave with actionable blueprints for scoping agent projects, a framework for calculating expected ROI before building, and practical techniques for optimizing agents in production. Whether you're a developer deploying your first agent, a data scientist exploring multi-agent architectures, or a technical leader making build-vs-buy decisions, this workshop provides the tools to move from prototype to measurable impact.

Feb 5th, 1:40 PM - 3:40 PM, ET

Hands on Training your RL Agent and Best Practices

Sanyam Bhutani - Partner Engineer, Generative AI Engineer | Meta

We will learn how to apply the best practices of Reinforcement Learning in a hands-on workshop where we will use OpenEnv from PyTorch as well as the latest developments in the field to train our RL agent.

The session will cover case studies and best practices of training AI Agents in the real world along with the latest developments in academia in a extremely hands on session

SecureYour Spot Now
‍

Learn from the Minds Shaping Agentic AI

Sammy Assefa

Senior VP, Head of AI | U.S. Bank

Full Bio

Coming Soon!

Paul Dongha

Head of Responsible AI & AI Strategy | NatWest Group

Full Bio

Coming Soon!

Misam Abbas

Staff AI Engineer | LinkedIn

Full Bio

Coming Soon!

Josh Reini

Developer Advocate | Snowflake

Full Bio

Josh Reini is a Developer Advocate for AI and Open Source at Snowflake, where he helps developers build scalable, trustworthy AI applications. Prior to Snowflake, Josh was at TruEra (acquired by Snowflake), where he became a core maintainer of TruLens, an open-source library for systematically tracking and evaluating LLM-based applications. Josh is a frequent speaker at major industry events, including PyData, Devoxx, AI_Dev, AI DevWorld, and AI Camp meetups, where he shares practical insights on building, evaluating, and deploying machine learning systems. Beyond the stage, he has taught thousands of students through courses on Coursera, DeepLearning.ai, Udemy, and DataCamp, and has advised on Trustworthy Machine Learning at Stanford University. With deep hands-on experience across open-source development, ML evaluation, and developer education, Josh is recognized as a trusted voice in the AI community, helping teams navigate the path from cutting-edge research to real-world impact.

Karen Zhou

Member of Technical Staff | Anthropic

Full Bio

Karen is a member of technical staff at Anthropic, where she works on developing product eval, RL environments, and multi-agent product features for Claude Code. She builds evaluation systems and feedback pipelines that assess how AI models behave in real-world software development scenarios, transforming user feedback into useful evals for model improvement. On the product side, she actively drives the development of swarm and multi-agent functionality that enables multiple AI agents to collaborate on complex software engineering tasks. Prior to Anthropic, Karen worked at Meta on large language models.

Matan-Paul Shetrit

Director of Product , a leader and pioneer in enterprise AI | Writer

Full Bio

Matan-Paul Shetrit is the Director of Product at Writer, a leader and pioneer in enterprise AI. With over 16 years of experience in product management, strategy, and economics, Matan has led product teams at A.Team, Brex, Flexport, and Square—driving innovative offerings that blend cutting-edge technology with deep market insight. Before joining Writer, Matan served as the Head of Product at A.Team, steering the platform's strategic roadmap to connect world-class tech talent with high-growth companies. At Brex, he was instrumental in launching card product offerings and partnership initiatives that significantly increased GMV. Earlier in his career, Matan led initiatives at Flexport, unlocking real-time supply chain visibility through novel freight marketplaces, and oversaw Square's developer platform, driving a 100x increase in transaction volume. Matan's background also includes policy and financial roles at Israel's Ministry of Finance and KCPS & CO, where he delivered economic analyses, risk strategies, and large-scale investment models. A member of the World Economic Forum's Global Shapers Community in San Francisco, Matan is passionate about leveraging AI and data-driven solutions to create tangible impact for businesses and society at large.

Sydney Runkle

Software Engineer | LangChain

Full Bio

Sydney Runkle currently works at LangChain. She leads open source development on LangGraph, a Python (and TS) library used to build, run, and deploy AI agents. Previously, she worked at Pydantic, where she helped maintain open source libraries such as Pydantic (Python's leading data validation library) and PydanticAI (another agent-building framework). Her open source work largely centers on driving release cycles informed by community demand and designing innovative abstractions catering to emerging trends with LLMs. Sydney particularly passionate about developer experience and documentation. Her journey in software engineering began early—she started working at startup companies at age 15 and graduated with BS in Computer Science from the University of Wisconsin-Madison at 20. In her free time, she loves to run, lift, and listen to podcasts. As of late, she has been particularly interested in ""Hard Fork"" from the NYT and ""The AI Engineer"" Podcast.

Leonardo De Marchi

VP of Labs | Thomson Reuters

Full Bio

Leonardo De Marchi holds a Master degree in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks and Manchester United. He now works in Thomson Reuters as VP of Labs and also provides consultancy and training for small and large companies. His previous experience includes being Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through acquisition and an IPO.

Andrea Kropp

Applied AI Engineer | LandingAI

Full Bio

Andrea is an Applied AI Engineer at LandingAI with over 15 years of experience delivering end-to-end solutions that transform raw data into critical business insights. As a former Senior Director of Data Science & Machine Learning at Fortune 500 firm, she understands the challenges leaders face developing, deploying and maintaining ML-based solutions in an environment when talent is scarce and tool choice is overwhelming. Andrea loves being back in the data trenches working side-by-side with the scientists and engineers at our customer organizations to deliver robust visual AI solutions that address real needs. Andrea holds and MS and BS in Chemistry from the University of Michigan and UC Irvine, respectively.

Manoj Saxena

Founder & CEO | Trustwise

Full Bio

Manoj Saxena is the CEO and founder of Trustwise, a leading AI software company dedicated to helping enterprises build reliable, efficient, and sustainable AI systems with trust at their core. Called the “father of IBM Watson” and a pioneer of “Trusted Artificial Intelligence” for his work on building ethical AI systems, Manoj Saxena is a leading practitioner, educator, and investor at the forefront of responsible AI innovation. Saxena is also the founder and Executive Chairman of Responsible AI Institute a seven-year-old non-profit dedicated to adoption of Trustworthy and Ethical AI. Previously, he was the General Manager of IBM Watson and was Chairman of the Board at the US Federal Reserve Bank of Dallas, San Antonio where he served for six years in that role. Prior to IBM, Saxena was the founder and CEO of two venture-backed software companies which were acquired within a five-year span by Commerce One and by IBM. Over his career, he has built startups that have generated over $1.8 billion in exit value. Saxena is a Director of the Saxena Family Foundation and a Lecturer at University of Texas Austin where he teaches a course on Design of Ethical Artificial Intelligence systems. He is also a fellow contributor at Cambridge University on a program teaching ‘Responsible Leadership in an Age of AI’. In his part time, he is an avid auto racing enthusiast and has completed over 60,000 miles in track, endurance, and auto rally races around the world in his 1934 Alvis Speed 20, a 1972 Datsun 240z, and a 2009 Porsche 911 GT3RS. Saxena holds a post graduate degree in business administration from Michigan State University, and graduate degree in management sciences from the Birla Institute of Technology & Science in Pilani, India. Holder of 34 AI software patents.

Claire Longo

AI Researcher | Comet

Full Bio

Claire Longo is an AI leader and mathematician with over a decade of experience leading teams at Twilio, Opendoor, and Arize AI. Currently a Lead AI Researcher at Comet, she is also a speaker, advisor, YouTuber, and poker player dedicated to mentoring engineers and championing diversity in AI.

Kyle Stratis

Founder Stratis | Data Labs

Full Bio

Kyle Stratis is the founder and principal consultant of Stratis Data Labs, where he specializes in designing and implementing AI, data, and cloud strategies for early-stage startups and large enterprises alike. He also serves as VP of Engineering at The Sequel Institute, where he transforms cutting-edge neuroscience and AI research into robust, scalable software products that bridge the gap between academic innovation and real-world applications. Kyle is the author of AI Agents with MCP, published by O'Reilly Media, which provides both a deep understanding of the Model Context Protocol and practical guidance for building intelligent agents with Python. His expertise spans the full AI/ML stack—from agent architectures and LLM orchestration to production-grade MLOps pipelines—with a focus on making advanced AI capabilities accessible and actionable for organizations at any stage of their AI journey. Prior to founding Stratis Data Labs, Kyle held engineering and technical leadership roles where he developed expertise in distributed systems, cloud infrastructure, and data engineering, bringing a uniquely holistic perspective to AI implementation challenges.

Cameron Royce Turner

Founder and CEO | TRUIFY.AI

Full Bio

Cameron Turner is founder and CEO of TRUIFY.AI, serving the US Fortune 500 with AI solutions. Drawing from 30 years experience in enterprise data, including the founding of two companies (ClickStream, acq. Microsoft in 2009 and Datorium, acq. Kin+Carta (LON:KCT) in 2021) Cameron brings a wealth of hands-of experience in leading teams to deploy solutions that uniquely fit the technology and culture of his clients. Cameron also serves as General Partner of Oxonian Ventures, a VC fund investing in Oxford University graduates, and volunteers with the Venture Studio at the Center for Entrepreneurial Studies at Stanford University. Cameron received his BA from Dartmouth College, MBA from Oxford University and MS in Statistics/AI from Stanford University.

Zain Hasan, PhD

Staff AI/ML Engineer - DevRel | Together AI

Full Bio

Zain Hasan has experience spanning academia, startups, and the tech industry. Trained as an engineer and data scientist, he completed his undergraduate and graduate work at the University of Toronto, focusing on AI-powered technologies. He began his career by founding a digital health startup that used machine learning to monitor chronically ill patients. He later worked as a Senior Data Scientist and AI/ML Engineer in both consulting and product-focused roles, including at Weaviate, a leading vector database company, and Together AI, a generative AI cloud provider. A passionate advocate for open-source software, education, and community, Zain has taught at the University of Toronto and delivered technical talks at conferences across North America and Europe. His work centers on bridging the gap between cutting-edge research and real-world deployment of AI systems.

Sara Zanzottera

Senior Developer | BNP Paribas

Full Bio

Sara Zanzottera is a Senior Developer at BNP Paribas. She worked on several GenAI projects such as autonomous voice agents, multimodal chatbots, RAG applications, and many more. She was also a core maintainer of Haystack, one of the most mature open-source LLM frameworks. She started her career at CERN as a Python software engineer on the particle accelerator’s control systems.

Harpreet Sahota

Hacker-in-Residence | Voxel51

Full Bio

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in Vision Language Models, Visual Agents, Multimodal Retrieval, Document Visual AI, and Robotics.

Sanyam Bhutani

Partner Engineer Generative AI Engineer at Meta

Full Bio

Sanyam Bhutani is a Partner Engineer at Meta. Prior to his current role, he was a Senior Data Scientist at H2O.ai. He also previously worked at Weights & Biases and had another tenure at H2O.ai. Beyond his corporate work, Sanyam is the host of the podcast "Chat with Data Science" (CTDS.Show). He is also an International Fellow of fast.ai and holds the esteemed title of Kaggle Grandmaster.

João (Joe) Moura

CEO at CrewAI

Full Bio

João is the CEO of crewAI, with over 20 years of experience with Software Engineering,previously, as Director of AI Engineering at Clearbit, he transformed AI into a core profit driver, growing a thriving user base and spearheading advancements in large-scale vector databases. João also founded Urdog, an IoT startup, where he developed a smart collar for dogs and managed all aspects of the business. With extensive experience in engineering leadership roles at Toptal and Packlane, he specializes in building high-performing teams and implementing scalable AI and machine learning solutions. João holds an MBA in Information Technology from FIAP and completed executive leadership training at NYU Stern.

Sheamus McGovern

Founder of ODSC, Head of AI and VP - Cortical Ventures

Full Bio

Sheamus McGovern is the founder of ODSC (The Open Data Science Conference). He is also a software architect, data engineer, and AI expert. He started his career in finance by building stock and bond trading systems and risk assessment platforms and has worked for numerous financial institutions and quant hedge funds. Over the last decade, Sheamus has consulted with dozens of companies and startups to build leading-edge data-driven applications in finance, healthcare, eCommerce, and venture capital. He holds degrees from Northeastern University, Boston University, Harvard University, and a CQF in Quantitative Finance.

Holt Skinner

Developer Advocate at Google Cloud

Full Bio

Holt has led the creation of numerous educational series on the Google Cloud Tech YouTube channel and manages the Google Cloud Generative AI GitHub repository, delivering practical resources and expert insights. With a passion for simplifying developer workflows, Holt actively engages with the global developer community to gather feedback and drive continuous improvement in AI technologies. Beyond his work in tech, Holt is also an accomplished classical singer who regularly performs in concerts across the United States and Europe.

Ivan Lee

CEO / Founderat Datasaur

Full Bio

Ivan Lee graduated with a Computer Science B.S. from Stanford University, then dropped out of his master’s degree to found his first mobile gaming company Loki Studios. After raising institutional funding and building a profitable game, Loki was acquired by Yahoo. Lee spent the next 10 years building AI products at Yahoo and Apple and discovered there was a gap in serving the rapid evolution of Natural Language Processing (NLP) technologies. He built Datasaur to focus on democratizing access to NLP and LLMs. Datasaur has raised $8m in venture funding from top-tier investors such as Initialized Capital, Greg Brockman (President, OpenAI) and Calvin French-Owen (CTO, Segment) and serves companies such as Google, Netflix, Qualtrics, Spotify, the FBI and more.

Sinan Ozdemir

AI Author and Educator

Full Bio

Sinan Ozdemir is a mathematician, data scientist, NLP expert, lecturer, and accomplished author. He is currently applying my extensive knowledge and experience in AI and Large Language Models (LLMs) as the founder and CTO of LoopGenius, transforming the way entrepreneurs and startups market their products and services. Simultaneously, he is providing advisory services in AI and LLMs to Tola Capital, an innovative investment firm. He has also worked as an AI author for Addison Wesley and Pearson, crafting comprehensive resources that help professionals navigate the complex field of AI and LLMs. Previously, he served as the Director of Data Science at Directly, where my work significantly influenced their strategic direction. As an official member of the Forbes Technology Council from 2017 to 2021, he shared his insights on AI, machine learning, NLP, and emerging technologies-related business processes. He holds a B.A. and an M.A. in Pure Mathematics (Algebraic Geometry) from The Johns Hopkins University, and he is an alumnus of the Y Combinator program. Sinan actively contribute to society through various volunteering activities. Sinan's skill set is strongly endorsed by professionals from various sectors and includes data analysis, Python, statistics, AI, NLP, theoretical mathematics, data science, function analysis, data mining, algorithm development, machine learning, game-theoretic modeling, and various programming languages.

Dr. Ali Arsanjani

Director, Applied AI, Google Cloud

Full Bio

Dr. Ali Arsanjani is the Director of Applied AI Engineering at Google Cloud, and Head of the Global AI Center of Excellence, leads GenAI strategic co-innovation, thought leadership & alliances. His team specializes in co-innovation with ISV and GSI partners as they run, integrate and build on GCP across the ML Lifecycle. Ali also works closely with product management to shape the direction of Google's AI and analytics offerings from a cloud perspective. Ali is an Adjunct Prof at San Jose State University & the University of California, San Diego, and advises students in the Masters in Data program and the Data Science Institute, respectively.

Submit Your Session

ALERT: NEW SESSIONS CONFIRMED

WEEK 1 STARTS IN 9 DAYS!

JAN 21 - FEB 5 I 3-WEEK HANDS-ON VIRTUAL SUMMIT

*** EARLY BIRD ENDS FRIDAY ***

4

DAYS

23

HOURS

59

MINUTES

ARCHITECTING THE AGENTIC FUTURE

30+

Expert Instructors

50+

Workshops & Demos

1k+

Builders, Engineers, & Innovators

$2,500

AI Platform Credits

Preliminary Schedule Overview

All sessions are scheduled in Eastern Time (ET), beginning at 12:00 PM and concluding around 5:30 PM ( 9:00 AM–2:00 PM Pacific Time (PT)

Week 0 - Introductory Workshops

Week 1 - Foundation

Week 2 - Implementation

Week 3 - Scale

SecureYour Spot Now‍

Speakers & Instructors

Learn from the Minds Shaping Agentic AI

Sammy Assefa

Senior VP, Head of AI | U.S. Bank

Paul Dongha

Head of Responsible AI & AI Strategy | NatWest Group

Misam Abbas

Staff AI Engineer | LinkedIn

Josh Reini

Developer Advocate | Snowflake

Karen Zhou

Member of Technical Staff | Anthropic

Matan-Paul Shetrit

Director of Product , a leader and pioneer in enterprise AI | Writer

Sydney Runkle

Software Engineer | LangChain

Leonardo De Marchi

VP of Labs | Thomson Reuters

Andrea Kropp

Applied AI Engineer | LandingAI

Manoj Saxena

Founder & CEO | Trustwise

Claire Longo

AI Researcher | Comet

Kyle Stratis

Founder Stratis | Data Labs

Cameron Royce Turner

Founder and CEO | TRUIFY.AI

Zain Hasan, PhD

Staff AI/ML Engineer - DevRel | Together AI

Sara Zanzottera

Senior Developer | BNP Paribas

Harpreet Sahota

Hacker-in-Residence | Voxel51

Sanyam Bhutani

Partner Engineer Generative AI Engineer at Meta

João (Joe) Moura

CEO at CrewAI

Sheamus McGovern

Founder of ODSC, Head of AI and VP - Cortical Ventures

Holt Skinner

Developer Advocate at Google Cloud

Ivan Lee

CEO / Founderat Datasaur

Sinan Ozdemir

AI Author and Educator

Dr. Ali Arsanjani

Director, Applied AI, Google Cloud

*** EARLY BIRD ENDS FRIDAY ***

4

DAYS

23

HOURS

59

* EARLY BIRD ENDS FRIDAY *

SecureYour Spot Now
‍

* EARLY BIRD ENDS FRIDAY *

Already have ODSC AI Pass?
‍
Claim your Agentic AI Pass with this form
‍

Paid Passes Include $2,500 in Credits
‍

Partner With Us
‍