AI Con USA 2025 - LLMs
Sunday, June 8
Fundamentals of AI—ICAgile Certification (ICP-FAI)
Monday, June 9
Getting Started with AI and Machine Learning
Are you a software professional who would like to learn to use AI and machine learning (ML), but don't know how to get started? One of the best ways to get into ML is by designing and completing small projects. Although you will ultimately need to understand the fundamentals of AI/ML, there's no reason why you can't learn foundational terms, concepts and principles as you put them into practice. Join Dionny Santiago as he introduces you to the world of applied machine learning. Dionny will guide you through a series of ML projects end-to-end, enabling you to gain experience with creating...
Become an AI Power User
NewImpostering a bit in the AI-verse? Overwhelmed by daily AI announcements? Unsure you're using AI most effectively? Tiny bit of FOMO? We've got you covered! In this workshop, we'll help you become an AI Power User. Become a boss at your job, whatever your role or industry! We'll show you where AI shines and where you'll want to be careful, plus toss you lots of hands-on practice. In our time together, we'll help you pinpoint YOUR niche, build a custom AI assistant, and develop a comms strategy to show off your new skills. You'll walk out with cutting-edge knowledge, a prompt library...
Introduction to RAG Applications: Building Conversational AI for Domain-specific Search
NewThis beginner-friendly workshop introduces participants to the fundamentals of Retrieval-Augmented Generation (RAG) applications. Using a pre-configured Docker environment featuring Python, Elasticsearch for vector storage, and OpenAI as the LLM, attendees will learn how to build a RAG-powered conversational portal. Throughout the session, participants will create a RAG application to consume and query a sample dataset of Washington State regulation documents. Replace these sample documents with your own PDF files, and you’ll interact with your data in no time! By the end, attendees will...
Tuesday, June 10
Prompt Engineering for Software Practitioners
With the sudden rise of ChatGPT and large language models (LLMs), practitioners are using these tools for all aspects of engineering. This includes leveraging LLMs for creating software artifacts such as requirements documents, source code, and tests; reviewing them for issues and making corrective suggestions, and analyzing or summarizing results or outcomes. However, if LLM's are not fed good prompts describing the task that the AI is supposed to perform, their responses can be inaccurate and unreliable. Join Tariq King as he teaches you how to craft high-quality AI prompts and...
A Quality Engineering Introduction to AI and Machine Learning
Although there are several controversies and misunderstandings surrounding AI and machine learning, one thing is apparent — people have quality concerns about the safety, reliability, and trustworthiness of these types of systems. Not only are ML-based systems shrouded in mystery due to their largely black-box nature, they also tend to be unpredictable since they can adapt and learn new things at runtime. Validating ML systems is challenging and requires a cross-section of knowledge, skills, and experience from areas such as mathematics, data science, software engineering, cyber-security,...
Image Classification using LLMs and Transfer Learning
Large language models, like Generative Pre-trained Transformers (GPTs) to create textual content in ChatBots and other Generative AI applications, have garnered much attention recently. However, not all data is textual. Another important use of LLMs is for image processing to address real-world problems such as: real-time object recognition, classification of images, and generation of modern art. Jeffery Payne will explore how large language models for images (also known as visual language models - VLMs) can be used for image classification, object detection, image capture generation, and...
AI Deep Dive: Exploring AWS Using Real-World Scenarios
Deepen your AI and machine learning expertise using AWS in an Immersive, hands-on workshop. You’ll use real-world AI challenges while leveraging AWS services like Amazon SageMaker, Bedrock, and Lambda to build and optimize AI-driven solutions. As the session unfolds, new constraints and data anomalies will emerge, mirroring the complexities of real-world AI/ML implementation. Gain insight into how AI solutions perform under evolving conditions, learning to adapt, optimize, and troubleshoot unexpected challenges. Learn the importance of collaboration, strategic thinking, problem-solving,...
Wednesday, June 11
Building Reliable AI Agent Flows
AI agents are revolutionizing how we interact with software, but their reliability remains a critical challenge. In this talk, Jason Arbon explores the key principles and techniques for designing AI agent flows that are predictable, testable, and robust. Attendees will learn how to structure AI-driven interactions to minimize failure points, leverage validation mechanisms, and integrate automated testing strategies to ensure smooth execution. Drawing from real-world applications and lessons learned in AI-driven software testing, this session will provide practical insights for engineers,...
Using GenAI to Advance Azure AIOps
In today’s rapidly evolving digital landscape, maintaining high service quality is crucial. To achieve this, Microsoft is leveraging cutting-edge technologies such as Generative AI and Large Language Models (LLMs) to enhance service reliability and developer productivity. LLMs excel at understanding and reasoning over large volumes of data. They can generalize across diverse tasks and domains, making them invaluable for generating models, insights, and automating intricate tasks. By integrating LLMs and Generative AI into the complex domains of incident response and root cause analysis,...
Testing Powered by AI/ML Synthetic Test Data: A Game Changer
The session covers a testing approach that utilizes a new age Test Data Management (TDM) technique which learns from production data. Machine learning analyzes the data to create a model capable of generating synthetic data with identical source data attributes. Multiple learning iterations refine the model, enhancing its accuracy with each cycle. The data model incorporates security measures like differential privacy, enabling safe movement to lower environments. Later, generative AI leverages this model to produce desired volumes of test data for various testing types, including...
Real-World Open Source Agentic Testing Framework: TestZeus
Test automation is evolving from manual scripting to AI-driven collaboration, where AI agents work together to ensure reliable test execution. This presentation introduces TestZeus, an open-source framework that leverages LLMs to transform Cucumber/Gherkin specifications into automated tests. Robin Gupta will explore its architecture and demonstrate how it handles common challenges like shadow DOMs and iframes. Learn how to implement and debug this next-generation framework, positioning yourself at the forefront of intelligent test automation. Join Robin to discover how TestZeus can...
Powering Complex Solutions with Agentic Systems
This session explores the revolutionary potential of agentic systems—autonomous agents equipped with diverse tools to tackle multifaceted tasks effectively. By integrating tools, agentic workflows enable intelligent, adaptive solutions to complex challenges. Apurva will start with an introduction to agentic systems, highlighting their ability to utilize various tools dynamically to achieve goals with minimal human intervention. Through real-world case studies, she will demonstrate how tools like APIs, databases, and external services are orchestrated within these systems to simulate...
Unlocking Agentic AI Superpowers in the Quantum Multiverse
Step into the future of AI with an immersive dive into the cutting-edge world of AI-Augmented GenAI and how it intercepts with Quantum technologies. This session explores the intersection of multi-threaded AI workflows and the powerful anomaly detection capabilities made possible by Quantum-inspired computing. Discover the latest trends in ModelOps, where agile deployment strategies for domain-specific generative AI models are accelerating innovation in industries ranging from healthcare to defense. Jonathon will uncover how GraphRAG (Graph Retrieval-Augmented Generation) is...
Thursday, June 12
RAG Has Evolved - Enhance Your RAG Pipeline with These Concepts
The majority of businesses today can set up a fundamental RAG pipeline that effectively handles most use cases. However, this basic setup eventually reaches its limitations in terms of functionality and accuracy, hindering further advancements. Matt Payne aims to detail the necessary pipeline components for building advanced RAG pipelines. For each component, he will explain the what, when, why, and how and provide real-world examples. Key areas of focus include leveraging tools and function calling, which enables you to create a systematic approach to using knowledge from multiple sources...
Empathy in Code: Balancing Emotional Intelligence with Ethical Boundaries in AI
As AI systems increasingly support the social and emotional well-being of humans, the integration of human-like interactions presents both opportunities and significant risks that necessitate the use of trauma-informed principles in design. This session examines the delicate balance between creating emotionally intelligent AI and maintaining essential ethical boundaries. Join Megs to explore critical decisions in AI development: when emotional support should be provided versus redirected to human professionals, how to establish clear limitations in AI capabilities, and methods for...