Join us for a power-packed night of learning, sharing, and networking at AI Dev Day - Seattle. We are excited to bring the AI developer community together to learn and discuss the latest trends, practical experiences, and best practices in the field of AI, LLMs, generative AI, and machine learning.

In addition to the tech talks, there will be plenty of opportunities to network with AI developers, live demos by AI startups, panel discussion, and career opportunities.

Agenda:
- 5:00pm~5:50pm: Checkin, food/drink and networking
- 5:50pm~6:00pm: Welcome, Community update
- 6:00pm~8:00pm: Tech talks, and panel
- 8:00pm~9:00pm: Q&A and Open discussion

Tech Talk 1: Evaluating LLM Agents
Speaker: Garett Tok @TruEra
Abstract: In a LLM-powered autonomous agent system, LLM functions as the agent’s brain by using planning and inference to decide what tools to use and how. As requests to your agent drift, evaluation is needed to identify gaps in tool coverage and keep the agent performing. This talk will cover the basics of building an LLM agent and how to evaluate it with open-source TruLens

Tech Talk 2: AutoGen: Multi-Agent Framework for Large AI Models
Speaker: Beibin Li @Microsoft
Abstract: Large Language Models (LLMs) and Large Multimodal Models (LMMs) demonstrate promising capabilities in problem solving and human-like conversation. However, orchestrating large models for real-world applications remains a challenge. Microsoft’s AutoGen framework is a pioneering solution to this challenge by introducing a multi-agent conversation framework. It assists developers in constructing AI workflows, simplifying tool orchestration, and automating complex tasks. This talk will explore the core functionalities of AutoGen, illustrating its multi-agent conversations that enhance accessibility and efficiency across a broad spectrum of tasks and industries, paving the way for next-generation AI applications.

Tech Talk 3: Towards Effective LLM Observability
Speaker: Cam Young @Arize AI
Abstract: In this session, we will demonstrate how to leverage LLM observability to evaluate LLM responses, pinpoint where to improve with prompt engineering, and identify fine-tuning opportunities using vector similarity search.

Speakers/Topics:
Stay tuned as we are updating speakers and schedules.
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Venue:
LeRoux Conference Center/Student Center 160, Seattle University, 901 12th Ave, Seattle, WA 98122
Driving/Parking: Room 160. The building is the "STCN" on the Campus Map. "P2" is for visitors parking.
Full parking/driving details, carpool requests, etc.. are posted in the Slack channel ("seattle" channel)

Lucky draw
We will raffle winners for prizes during the event. To enter the lucky draw, "comment" the post on LinkedIn: LinkedIn Post

Sponsors:
We are actively seeking sponsors to support AI developers community.  Whether it is by offering venue spaces, providing food, or cash sponsor. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure through post-event emails sent to our extensive membership base of 20,000+ local or 300K+ developers worldwide.

Community on Slack
- Event chat: chat and connect with speakers and attendees
- Sharing blogs, events, job openings, projects collaborations
Join Slack (search and join the #seattle channel)