AI Con USA 2025 - AI Application Development
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
Clean Your Filthy RAGS! Optimizing, Accelerating, and Evaluating RAG Applications
NewRetrieval-Augmented Generation (RAG) applications are becoming essential for companies, combining AI with real-time data retrieval to enhance customer experiences. While Large Language Models (LLMs) handle general conversation well, they struggle with domain-specific, up-to-date information, often producing inaccurate or unhelpful responses. This workshop will empower participants with the necessary skills to optimize RAG applications using existing best practices. Justin will walk through integrating RAGAS, a framework designed to evaluate, monitor, and fine-tune the performance of RAG...
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,...
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
Test Machina: Demystifying AI-Driven Testing Agents
Software vendors and practitioners are using artificial intelligence (AI) and machine learning (ML) to create a new wave of test automation tools. Such tools leverage autonomous and intelligent agents to explore, model, reason and learn about a software product. But how do these testing agents really work? Is this technology any good? And can we really trust them to validate software? Tariq King will introduce you to the world of agentic AI and discuss its benefits, challenges and other limitations. Learn how AI test agents use AI/ML technologies to mimic human testing activities such as...
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...
Navigating AI Governance: Building Trust in a Regulated Future
As artificial intelligence systems increasingly influence critical decisions across industries, ensuring compliance with evolving governance and regulatory standards is both a challenge and a necessity. This presentation will explore the complexities of AI governance, focusing on balancing innovation with compliance in a rapidly changing regulatory environment. Vijay Panwar will examine real-world challenges such as bias mitigation, data privacy adherence, and ethical transparency, providing actionable strategies to design AI systems that comply with global standards like GDPR and emerging...
Thursday, June 12
Advancing Biotechnology: AI's Role in Modern Applications
This session explores the transformative impact of AI on biotechnology applications, including drug discovery, genetic sequencing, and digital pathology. It delves into the modernization of testing and verification practices, highlighting the intersection of AI and cybersecurity. Attendees will gain insights into addressing challenges associated with limited training datasets in regulated environments and strategies for developing robust applications. Practical lessons learned and actionable insights will be shared to empower participants in navigating the evolving AI landscape in...
Continuous Testing for AI Applications
In the era of artificial intelligence, software testing has evolved from a finite phase in development to an ongoing, dynamic process of monitoring. Unlike traditional deterministic systems, AI-driven applications operate probabilistically, introducing variability and uncertainty in outputs even with consistent inputs. This paradigm shift requires a rethinking of testing strategies, moving towards continuous monitoring to ensure performance, fairness, and reliability in production environments. This session will explore how QA teams can integrate AI-specific methods, anomaly detection, and...
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...
Tool Calling is Not Just Plumbing for AI Agents
Tool calling is more than just a technical detail—it’s the most important piece of how AI agents get things done. It allows agents to connect to systems, access data, and perform tasks effectively. Building good tools is very similar to building good APIs, as they need good design for things like authentication and security. But building good tools requires a bit more than knowledge about building APIs.
In this session, we’ll explore how tool calling works, why it matters, and how to do it right. You’ll learn different ways to build tools that help agents connect to APIs, databases...
Amazing Ways Retailers Are Using Generative AI
Generative AI is transforming the retail industry by enabling innovative approaches to customer engagement, personalization, and operational efficiency. Retailers are leveraging AI-driven tools to create personalized shopping experiences, from generating tailored product recommendations to crafting dynamic marketing content. In e-commerce, generative AI enhances virtual try-ons and product design, allowing for more interactive and immersive customer journeys. Additionally, retailers use AI for predictive inventory management, automating supply chain decisions, and optimizing logistics....
Shadow Vulnerabilities in AI/ML Data Stacks - What You Don’t Know CAN Hurt You
The adoption of open-source AI software introduces a new family of vulnerabilities to organizations. Some components in AI, like model serving, include Remote Code Execution (RCE) by design, like when loading pre-trained models from external sources. Traditional SCA and SAST approaches are not built for the AI ecosystem leaving a huge & insecure attack surface. The irony is that in the AI ecosystem, security issues such as remote code execution are actually a feature and not a bug, often specified explicitly in the docs, which most devs don’t read. AI models are often downloaded from...
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...