I will talk about the validation and monitoring of AI agents using the example of a mobile application that interacts with a multi-agent system via OpenAPI. I will demonstrate practical approaches to testing agent logic, methods for collecting performance metrics, and setting up an observability system. I will share my experience in tracking agent behavior in real time, detecting anomalies, and ensuring the reliability of a multi-agent architecture in production.

In this talk, we’ll explore why good developers won’t be replaced by AI — but their roles will definitely change. Why the classic “I just write code” mindset is no longer enough. And what the profile of a senior+ developer looks like in this new reality: multidisciplinary, with product thinking, strong soft (core) skills, and the readiness to act as a tech advisor to the business.

Oleksii Minakov and Oleksandr Krakovytskyi will face off in a spectacular battle to showcase the most striking and unexpected use cases of generative artificial intelligence tools — live on stage. Get ready for unconventional scenarios, creative experiments, and impressive real-world AI applications that will captivate both beginners and seasoned professionals. The goal is not just to amaze, but to expand your understanding of what modern AI is truly capable of.

The traditional approach of “AI is just a tool” limits AI to a supporting role, is outdated, and seems outright amusing in the context of the emerging boom of AI agents. Fully unlocking the potential of modern AI systems requires interactive, two-way collaboration and partnership. Let’s explore various models of human-AI interaction that are transforming work paradigms: the “cyborg” and “centaur” models, the “ensemble,” the “author-driver” and “resonator,” the “cybernetic colleague,” the “thinking partner,” and others. How can we avoid the “falling asleep at the wheel” effect or disengaged AI interaction? Every employee becomes the CEO of a startup composed of a mini-team of AI agents — but what is the optimal number of AI agents per employee?

I’ll talk about how the approach to writing changes when a generative AI becomes your co-author. I’ll share my personal experience of writing a book about generative AI — with its help — including ethical dilemmas, cognitive challenges, and unexpected insights. I’ll explain why the process took ten times longer but brought a hundred times more experience. I’ll also show how I worked with terminology and how, in parallel, I developed practical recommendations for using generative AI in programming, education, and other fields.

I will discuss modern video generation capabilities from text prompts and AI-assisted editing, leveraging my 17 years of video production experience. I will showcase key platforms and tools, share case studies of integrating AI into creators’ and product managers’ workflows, outline product opportunities and workflows for developers and video makers, and highlight priority directions for the development of AI-based video services.

Can you trust the cloud? Confidential Computing enables data protection even in fully controlled environments.

A practical case of using a computer vision system for automated visual inspection in a pharmaceutical production line. The system ensures the quality and consistency of vial contents, reducing human error and improving efficiency in a highly regulated environment.

As an infrastructure provider, we often see that potential clients are somewhat disoriented when it comes to choosing the right accelerators. The technology evolves rapidly, and questions like “What’s out there?”, “How do these cards differ?”, and “Which ones are better?” are completely valid. But the selection criteria are far from simple. In this talk, we’ll explain key concepts such as compute-bound vs memory-bound models, arithmetic intensity, and model quantization—factors that are crucial when choosing the right hardware for your workload.