Agile + DevOps USA 2024 - AI/ML
Sunday, October 13
Fundamentals of AI—ICAgile Certification (ICP-FAI)
Monday, October 14
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,...
Leveraging Generative AI for Software Productivity
Executive leaders across the globe have been asking a relatively simple yet profound question: Can we leverage generative AI to transform our business, enterprise, or industry? For software-based companies, focus has either been on differentiating their product and service offerings using this new technology. But how about leveraging generative AI to improve team productivity and efficiency? This may be possible but how do you measure its success? What are some of the key use cases within business analysis, development, and testing that software teams can use? Are there any pitfalls...
Essential Test-Driven Development with AI/LLM Assist: A Hands-On Workshop
Will AI take over developer and tester roles? Rob's investigations found that an AI/LLM bot can write effective implementations but will need very clear, descriptive specifications. Yes, we humans will need to write the tests first! Test-Driven Development (TDD) has allowed developers to do just that—to "think in tests"—for over 25 years. TDD combines engineering specification, developer testing, coding, and design in a fast feedback cycle that greatly reduces defects, debugging, and rework. Test-driven teams write a failing automated test that defines new behavior, then the "...
Tuesday, October 15
Supercharge Your Workflow: To GitHub and Beyond
Whether you are new or experienced with GitHub this class is for you! Supercharging your workflow caters to anyone who wants to enhance their agile and DevOps process with the capabilities of GitHub. GitHub has long been the premier site for open-source projects and is now turning a pivotal corner into becoming the predominant platform for all aspects of the development lifecycle. Some examples of this include; protecting company code through various GitHub Products or curating marketplace actions and workflows prior to use. This tutorial will look at how to leverage GitHub Actions (CI/CD...
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 Kaushal Dalvi as he introduces you to the world of applied machine learning. Kaushal will guide you through a series of ML projects end-to-end, enabling you to gain experience with creating...
MLOps: DevOps for Machine Learning
Much attention is given to machine learning model training and testing in the industry. While these activities are essential for producing a production-ready machine learning model, organizations face some critical business challenges that must be addressed when building and testing machine learning models. Things like the reproducibility of results, accuracy of predictions, reusability of components, and trackability of experimentation are all vital to the success of any application. The term MLOps has emerged as a method for applying DevOps practices and automation to the machine...
Wednesday, October 16
Everything Old Is New Again: Using What We Already Know for a Safer Future
Our world is filled with complexities and unknowns, and when these collide with emerging technologies, the resulting risk seems insurmountable. We accept this increased risk as a cost of using the new technology, assuming that previous lessons learned don’t apply and that a blank slate is required to gain the most benefit. However, this never turns out to be true. Time and time again, we realize that much of what we already know is still relevant to these emerging technologies, regardless of how advanced or paradigm-shifting they are. This is good news for reducing the risk in innovation...
From Vision to Velocity: Accelerating Agile Testing with Generative AI
In the rapidly evolving landscape of agile and DevOps, traditional methods of testing business-facing features often struggle to keep pace with the demands for faster and more thorough testing. However, the fusion of traditional testing wisdom with cutting-edge AI presents a unique opportunity to enhance software quality and delivery speed, offering innovative solutions to longstanding challenges. Join Philip Daye and examine key test design techniques—such as equivalence partitioning, boundary value analysis, decision table testing, and state transition testing—and explore how Generative...
AI & The Impact on How We Work
Our industry has been transformed by new technologies, radically changing how we work. Thirty years ago, deployment cycles took 3-5 years; today, they happen in seconds. This rapid pace is largely due to our focus on investing in tools that boost developer productivity. We're still driven to create tools that simplify developers' work and make it easier for others to join the field. Many companies are heavily invested in enhancing productivity. However, the abundance of productivity tools doesn't automatically lead to increased productivity. Companies need to examine and adapt their...
Panel: How AI is Revolutionizing the Entire SDLC
Artificial Intelligence is transforming the software development life cycle, reshaping processes, and redefining best practices across the board. This is not just a trend—it's a game-changer. Join our dynamic panel of top-tier experts representing Agile, DevOps, software testing, security, and product development as they dive into how AI is impacting everything from code to culture. What does this mean for your projects, teams, and career? Bring your questions, and together we'll explore the challenges and opportunities AI brings to software development. We’ll use Slido to collect your...
Thursday, October 17
MLOps for Responsible AI: Techniques for Ensuring AI Quality
With the rapid adoption of generative AI, more and more companies are infusing AI models and services into their products. However, many of these companies are likely to lose business and valuable revenue due to their lack of investment in MLOps. Typically, organizations developing AI systems have relied on training metrics like accuracy, precision and recall, but software quality goes beyond that. Now that the barrier to entry for AI tools is smaller, we need to set quality standards, test practices, and think about AI ethics and safety. Ensuring the quality of AI goes beyond traditional...
From Concept to Code: Leveraging LLMs for Agile Excellence
Unlock the next level of agile and XP development by integrating Large Language Models (LLMs) like ChatGPT and GitHub Copilot across the software development lifecycle. This presentation unveils how leveraging LLMs from initial ideation to final deployment transforms agile practices, enriching pair programming, test-driven development, and continuous integration with innovative AI capabilities. Learn to automate and refine development tasks, enhance specification clarity, and boost testing efficiency with ChatGPT, optimizing every phase of agile workflows for superior product quality and...
Are AI Assistants the Death of Programmers?
There is a lot of hype about Generative AI automatically creating software applications. Some see this as the death of the software engineering profession, while others believe AI technology will simply help increase the productivity of programmers. The reality is probably somewhere in the middle. This session explores this question and uses demonstrations of commercial and open-source AI assistants to show what is and is not possible with today's GenAI technology. A high-level discussion of how these models work will be included to give the audience some context for what they can and...