AI Con USA 2026 - Software Tester
Customize your AI Con USA 2026 experience with sessions for software testers.
Monday, June 8
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...
Human in the Loop
New"We love AI and use it for everything we do!" "We hate AI and will NEVER use it for anything ever, I swear to god!" Which camp are you in? This will be a question that will come up over and over in 2026 and beyond. If you use AI for EVERYTHING and think you can be mistaken for AI…has AI not already taken your job? We all need to get INTENTIONAL about our stance in the AI-verse. Have you thought deeply about what is a good activity for AI to lead on and what should be uniquely human? We are already seeing a premium price tag on in-person, uniquely human-to-human experiences, and this will...
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,...
Become an AI Power User
Impostering 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...
Tuesday, June 9
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...
AI-Enabled Building: Let the Robot Do the Work
NewTheory is great, but what about getting your hands dirty with some real problem-solving? Lets build your own AI Operating System that you'll take home and use immediately. Join Melissa Benua and Ryan Lee for a hands-on session where you'll construct a personalized AI toolkit that solves YOUR specific testing problems, regardless of your coding background. We'll start by deconstructing the modern software development lifecycle used by all tech companies to safely ship software solutions to their customers, and show you exactly where AI accelerates each phase. Then we'll prove a critical...
Strategies for Testing Autonomous AI and Multi-Agent Architectures
NewTesting Artificial Intelligence (AI) agents presents a paradigm shift from traditional software quality assurance. Unlike deterministic, rule-based applications, AI agents exhibit emergent behaviors, learn from their environments, and make autonomous decisions, making conventional test case design and execution insufficient. This tutorial will provide a comprehensive understanding of the unique challenges and advanced strategies required to effectively test single and multi-agent AI systems. Participants will learn how testing agents differ significantly from testing traditional software....
Agentic AI: From Rules to Reasoning
NewAI agents have existed for decades, but generative AI has fundamentally changed what agents can do and how they are designed and built. Come and explore the evolution of AI agents across two major waves. First, learn the foundations of Agentic AI through agents built using rules, heuristics, and traditional machine learning, examining where these approaches excel and why they struggle with complexity, ambiguity, and scale. Then dive into the second wave of agents powered by generative AI and multimodal large language models. These modern agents can reason, plan, use tools, and interact...
Wednesday, June 10
Will the Real Autonomous Agent Please Stand Up: What’s Real, What’s Not, and What You Actually SHOULD Be Investing in in the AI-Verse
If you’ve seen the news lately, the tech bros will have you believe that AI is both here to take your job and also your soul. On the other side, people are saying that we are in an AI-bubble, it’s all hype, and we don’t need to worry about it at all. Which is it? The truth is…it’s a little of BOTH. Dona will demystify what the latest buzzwords in AI (what is OpenClaw all about) and show you a roadmap for how you can AND SHOULD be using AI in your day-to-day life. You’ll learn how to set up an experiment framework for yourself, identify the workflows AI is actually good for, how to run the...
Why Your Agentic PR Never Gets Approved—Going from Vibe Coding to Agentic Engineering
You can write 100% of your code with AI, and only be 15% more productive. Want to know why? Solving the problem of moving faster as an engineer is about way more than code. You design, you problem solve, you discuss and communicate, you test, you shepherd the PR through review, you deploy, and you observe. So why are you being told you should be 10x faster now that AI can write code? David will discuss practical solutions for safely accelerating your entire workflow with AI. He will look at how to collaborate with PM, how to use AI planning, how to ensure validations are solid and builds...
Show Me the ROI: What Enterprise AI Actually Delivers in Year 4 - Panel
The hype cycle is over. The pilot graveyard is full. MIT research suggests that 95% of Generative AI implementations have little to no measurable impact on P&L. So what separates the 5% that actually deliver? In this no-fluff panel, practitioners from the front lines of enterprise AI — spanning automotive, cloud platforms, and the messy middle of real-world deployment — will have a candid conversation about what's working, what consistently stalls, and what it actually takes to move from experimentation to results.
The panel will discuss:
The use cases that outperform the hype...Thursday, June 11
Beyond the Chatbot: Building and Orchestrating Autonomous Security Agents
The next generation of security automation isn’t found in a chat interface—it’s found in Agents. While basic AI assistants can provide security advice and even remediate vulnerabilities, the real breakthrough for security teams lies in using an Agentic Workflow for security testing: the ability to build, customize, and orchestrate specialized agents that take ownership of the testing and remediation lifecycle. In this session, Jeffery Payne demonstrates how to move beyond conversational AI to create autonomous security agents using standardized formats compatible across tools like GitHub...
User-centricity for AI-assisted Test Engineers
Traditional software testing is fundamentally deterministic: the same inputs must always produce the same outputs. Yet many teams introduce AI into their testing without first defining the problem the AI is meant to solve, leading to brute-force experimentation and unreliable results. Google’s 2025 DORA report highlights that user-centricity is a prerequisite for AI success and that AI is most effective when it is pointed at a clear problem. AP shows you how that insight applies technically to testing. Before AI can be used as a testing tool, it must first be tested and understood in the...