AI Con USA 2025 - AI Real-World in Practice

Wednesday, June 11

Sarvani Sathish Kumar
Microsoft Corp
W2

Using GenAI to Advance Azure AIOps

Wednesday, June 11, 2025 - 11:00am to 11:45am

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,...

Apurva Misra
Sentick
W5

Powering Complex Solutions with Agentic Systems

Wednesday, June 11, 2025 - 11:50am to 12:35pm

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...

Bob Rapp
GM (General Motors)
W8

Moving from Reproducible Data Science to the World of LLM, GPT, RAG, and Hallucination

Wednesday, June 11, 2025 - 1:35pm to 2:20pm

We are moving from the world of reproducible data science (machine learning, area under the curve, a/b testing, model selection, model testing, model fitting and model drift to find the best way to run a data science organization) to being faced with the "Easy Button." This "Easy Button" is often wrong, has poor data protocols, and tries to please; without factual basis. Join Bob to explore ways to make the world better in the bridge from science to the new world of utterances. This session will include examples and experiences from IBM Watson, AI at GE Healthcare, AI at Microsoft, and...

Monalisha Singh
NetApp, Inc.
W11

Decoding the Black Box: Unlocking LLM Observability

Preview
Wednesday, June 11, 2025 - 2:25pm to 3:10pm

LLMs are revolutionizing AI, but their complexity and black-box nature can make it challenging to understand their behavior and ensure optimal performance. This session will demystify LLM observability, providing practical insights and best practices for gaining visibility into LLM interactions, performance, and security. Learn how to: discover the essential metrics to monitor for LLM health and performance, implement effective logging and tracing strategies to track LLM requests and identify bottlenecks, optimize LLM inference performance using profiling techniques, proactively...

Thursday, June 12

T2

Mastering Quality Engineering in the Age of AI

Preview
Thursday, June 12, 2025 - 10:50am to 11:35am

AI is transforming the software quality engineering industry by automating routine tasks and enabling smarter testing approaches. Its integration into software development has profoundly reshaped the field of Quality Engineering (QE). This presentation explores the evolving role of QE in the AI era, addressing the challenges, opportunities, and strategies for achieving excellence in AI-driven environments. By examining the intersection of AI and QE, it provides valuable insights into best practices for maintaining high-quality software and equips QE professionals with the knowledge...

Cy Khormaee
Attentive
T5

Continuous Testing for AI Applications

Thursday, June 12, 2025 - 11:40am to 12:25pm

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...