Yoga

Morning Yoga

K1

Nathan Hamiel
Kudelski Security

KEYNOTE | 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 because it means that we never really start from scratch. We begin our journey by examining how technological ghosts haunted previous technologies, showing the relevancy of already-known lessons. The journey continues to the current age of generative AI, examining the risks and challenges and how employing what we already know can lead to safer, more reliable systems and applications. In the end, we’ll see that by applying hard-won lessons to new technologies, we can ensure a safer, more reliable future.

W2

Cloud Engineering*

Clean Your Cloud with Cloud Custodian

Gene Gotimer, Praeses, LLC

W4

AI/ML*

From Vision to Velocity: Accelerating Agile Testing with Generative AI

Philip Daye, EMARKETER

ITP1

Industry Technical Presentation

AI-Driven Testing: Boosting Software Quality and Speed

Mason Henry, OpenText

W6

Agile & DevOps Testing*

Enhancing Agile and DevOps Practices: Leveraging Postman API Software for Enhanced Testing Efficiency in Tackling Real-World Challenges

Patrick Gladney, US Army Corps of Engineers

ITP3

Industry Technical Presentation

Bringing Back Test Design Thinking in Agile Development

Sai Sasidhar & Ravi Krishna, Muffins

K2

Jen Krieger
GitHub

KEYNOTE | 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 internal systems and processes, especially in decision-making and information sharing. This is where many companies stumble. They heavily invest in areas where developers are coding but neglect other crucial areas. The impact of these changes is significant for enterprise businesses, often with failure indicators appearing too late for recovery. Join Jen Krieger as she delves into these topics and prepares for the future of software development in an era of unprecedented speed.

W14

AI/ML*

Gen AI: A Co-Pilot to Better Value Sooner, Safer, and Happier in Digital Transformation

Paromita Sarkar, Voya Financials

W15

Architecture & Design*

Maximizing Observability in Cloud-Native Architecture: The Role of OpenTelemetry

Monalisha Singh, NetApp, Inc.

K3

Alison Wade
TechWell

KEYNOTE | Lightning Strikes the Keynotes

Throughout the years, Lightning Talks have been a popular part of the Agile + DevOps conferences. If you’re not familiar with the concept, Lightning Talks consists of a series of five-minute talks by different speakers within one presentation period. Lightning Talks are the opportunity for speakers to deliver their single biggest bang-for-the-buck idea in a rapid-fire presentation. And now, lightning has struck the Agile + DevOps keynotes. Some of the best-known experts in software engineering will step up to the podium and give you their best shot of lightning. Get multiple keynote presentations for the price of one—and have some fun at the same time.

Yoga

Morning Yoga

K4

Carlos Kidman
Qualiti

KEYNOTE | 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 metrics into attributes like usability and fairness, which need to be tested and measured using both manual exploratory and automated test strategies. Join Carlos Kidman as he covers the AI risks and biases that can happen throughout the development pipeline, demonstrate a few techniques to test a model's behaviors, security robustness, and fairness, and apply them against some real-world scenarios and state-of-the-art models. Come and learn new ideas for defining and testing responsible AI systems using quality attributes that resonate from a customer's perspective.

T1

Agile Implementation*

Designing Agile Plays in a Complex Organization

Desiree Lorell, United States Space Force

T2

Leadership*

5 Tools for Navigating Regulatory and Risk Mitigation in Agile Processes

Jennifer Wilhelmi & Natalia Kuzmina, S&P Global

T7

Leadership*

Top 10 Lessons I Learned for Leading Agile Teams

Chris Knobbe, Edward Jones

T8

DevOps Practices*

Containerization and Orchestration: Transforming Healthcare Apps with DevOps Automation

Sindhu Gandavarapu, Clareto

T11

Agile Implementation*

Scaling Agile at Visa: Navigating the Highs and Lows of Transforming a Financial Giant

Sannette Coetzee, Acolar, Inc.

T12

Leadership*

Reluctance to Relishing—Rolling Out DORA Metrics to Skeptical Teams

Kendra Schmid, WillowTree, a Telus Intl Company

ITP11

Industry Technical Presentation

AI-Assisted Development: Using GitHub Copilot and Other Tools to Accelerate Delivery

Jeffery Payne, Coveros