This talk presents an architectural approach to AI quality assurance in which a second AI system plays the role of a “judge,” replacing traditional testing methods. Using our real-world AI Calories Tracker an application that recognizes 5,000+ food photos every day, we will demonstrate how this unconventional strategy lets us manage risk effectively and boost trust in artificial intelligence.

We will analyze what actually works in the field of autonomous LLM agents, the existing limitations and their causes, research directions aimed at extending the duration of fully autonomous task execution, explore potential architectures of fully autonomous systems, economic autonomy of agents, and where we currently stand on the path toward achieving it.

Microsoft’s Vision. An overview of supply and demand, key trends in the development of artificial intelligence, as well as challenges in the corporate and public sectors.

Let's talk about the current state of AI investments, which products are attracting funding, whether it's a good time to invest now, and how to go about it.

We'll explore the key challenges of developing RAG-systems for the Ukrainian language. We'll discuss evaluation methods for such systems in specific domain areas, like consulting citizens on public services, and uncover practical insights and common "gotchas" that arise during implementation.

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?